DATA_PATH <- here("data/processed/syntactic_bootstrapping_tidy_data.csv") # make all variables (i.e. things that might change) as capital letters at the top of the scripts

ma_data <- read_csv(DATA_PATH)   %>%
  filter(language == "English",
         population_type == "typically_developing", 
         stimuli_modality == "video"|stimuli_modality == "animation",
         !is.na(mean_age))

ma_data
## # A tibble: 105 x 55
##       x1 coder unique_id link  grammatical_cla… paper_eligibili… short_cite
##    <dbl> <chr> <chr>     <chr> <chr>            <chr>            <chr>     
##  1     1 alan… arunacha… http… verb             include          Arunachal…
##  2     2 alan… arunacha… http… verb             include          Arunachal…
##  3     3 alan… arunacha… http… verb             include          Arunachal…
##  4     4 alan… arunacha… http… verb             include          Arunachal…
##  5     5 alan… arunacha… http… verb             include          Arunachal…
##  6     6 anjie arunacha… http… verb             include          Arunachal…
##  7     7 anjie arunacha… http… verb             include          Arunachal…
##  8     8 alan… bunger20… http… verb             include          Bunger, A…
##  9     9 alan… bunger20… http… verb             include          Bunger, A…
## 10    10 alan… bunger20… http… verb             include          Bunger, A…
## # … with 95 more rows, and 48 more variables: data_source <chr>,
## #   expt_num <chr>, expt_condition <chr>, dependent_measure <chr>,
## #   test_type <chr>, same_infant <chr>, language <chr>, mean_age <dbl>,
## #   productive_vocab_mean <dbl>, productive_vocab_median <dbl>,
## #   population_type <chr>, sentence_structure <chr>, agent_argument_type <chr>,
## #   patient_argument_type <chr>, verb_type <chr>, stimuli_type <chr>,
## #   stimuli_modality <chr>, stimuli_actor <chr>, presentation_type <chr>,
## #   character_identification <chr>, practice_phase <chr>,
## #   test_mass_or_distributed <chr>, n_train_test_pair <dbl>,
## #   n_test_trial_per_pair <dbl>, n_repetitions_sentence <dbl>,
## #   n_repetitions_video <dbl>, example_target_sentence <chr>,
## #   test_question <chr>, inclusion_certainty <dbl>, note <chr>, n_1 <dbl>,
## #   x_1 <dbl>, x_2 <dbl>, x_2_raw <dbl>, sd_1 <dbl>, sd_2 <dbl>,
## #   sd_2_raw <dbl>, t <dbl>, d <dbl>, d_calc <dbl>, d_var_calc <dbl>,
## #   es_method <chr>, unique_infant <chr>, test_method <chr>,
## #   agent_argument_type_clean <chr>, patient_argument_type_clean <chr>,
## #   adult_participant <chr>, data_source_clean <chr>

Data Overview

n_effect_sizes <- ma_data %>%
  filter(!is.na(d_calc)) %>%
  nrow()

n_papers <- ma_data %>%
  distinct(unique_id) %>%
  nrow()

There are 105 effect sizes collected from 30 different papers.

Here are the papers in this analysis:

ma_data %>%
  count(short_cite) %>%
  arrange(-n) %>%
  DT::datatable()

# Forest plot

ma_model <- rma(ma_data$d_calc, ma_data$d_var_calc)
ma_model
## 
## Random-Effects Model (k = 105; tau^2 estimator: REML)
## 
## tau^2 (estimated amount of total heterogeneity): 1.5214 (SE = 0.2340)
## tau (square root of estimated tau^2 value):      1.2335
## I^2 (total heterogeneity / total variability):   94.27%
## H^2 (total variability / sampling variability):  17.45
## 
## Test for Heterogeneity:
## Q(df = 104) = 783.8714, p-val < .0001
## 
## Model Results:
## 
## estimate      se    zval    pval   ci.lb   ci.ub 
##   0.5523  0.1273  4.3383  <.0001  0.3028  0.8018  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
forest(ma_model,
       header = T,
       slab = ma_data$unique_id,
       col = "red",
       cex = .7)

#funnel plot {.tabset} ## vanilla

ma_data %>% 
  mutate(color = ifelse(sentence_structure == "transitive", "red", "blue"),
         color_sample_size = ifelse(n_1 < 10, "red", ifelse(n_1 < 20, "orange", "yellow")),
         color_confidence = ifelse(inclusion_certainty == 1, "red", "black"))-> ma_data_funnel


ma_data_funnel %>% filter (abs(d_calc) < 5) -> ma_data_funnel_no_outlier

ss_colors <- ma_data_funnel$color
ss_colors_no_outlier <- ma_data_funnel_no_outlier$color 

ma_model_funnel <- rma(ma_data_funnel$d_calc, ma_data_funnel$d_var_calc)
ma_model_funnel_no_outlier <- rma(ma_data_funnel_no_outlier$d_calc, ma_data_funnel_no_outlier$d_var_calc)

f1<- funnel(ma_model_funnel, xlab = "Effect Size", col = ss_colors) 
legend("topright",bg = "white",legend = c("transitive","intransitive"),pch=16,col=c("red", "blue"))
title(main = "All effect sizes break down by sentence structure")

f2<- funnel(ma_model_funnel_no_outlier, xlab = "Effect Size", col = ss_colors_no_outlier) 
legend("topright",bg = "white",legend = c("transitive","intransitive"),pch=16,col=c("red", "blue"))
title(main = "effect sizes excluded outliers (abs <5) break down by sentence structure")

take int occount sentence structure?

ma_model_sentence_structure <- rma(ma_data_funnel$d_calc~ma_data_funnel$sentence_structure, ma_data_funnel$d_var_calc)
ma_model_no_outlier_ss <- rma(ma_data_funnel_no_outlier$d_calc~ma_data_funnel_no_outlier$sentence_structure, ma_data_funnel_no_outlier$d_var_calc)

f3 <- funnel(ma_model_sentence_structure, xlab = "effect size", col = ss_colors)

f3_b <- funnel(ma_model_no_outlier_ss, xlab = "effect size", col = ss_colors_no_outlier)

take int account sentence structure and age?

ma_model_ss_age <- rma(ma_data_funnel$d_calc~ma_data_funnel$sentence_structure + ma_data_funnel $mean_age, ma_data_funnel$d_var_calc)
ma_model_funnel_no_outlier_ss_age <- rma(ma_data_funnel_no_outlier$d_calc~ma_data_funnel_no_outlier$sentence_structure+ma_data_funnel_no_outlier$mean_age, ma_data_funnel_no_outlier$d_var_calc)



f4 <- funnel(ma_model_ss_age, xlab = "effect size", col = ss_colors)

f4_b <- funnel(ma_model_funnel_no_outlier_ss_age, xlab = "effect size", col = ss_colors_no_outlier)

Variable Summary

Continuous Variables

CONTINUOUS_VARS <- c("n_1", "x_1", "sd_1", "d_calc", "d_var_calc", "mean_age")

long_continuous <- ma_data %>%
  pivot_longer(cols = CONTINUOUS_VARS)

long_continuous %>%
  ggplot(aes(x = value)) +
  geom_histogram() + 
  facet_wrap(~ name, scale = "free_x") +
  labs(title = "Distribution of continuous measures")

long_continuous %>%
  group_by(name) %>%
  summarize(mean = mean(value),
            sd = sd(value)) %>%
  kable()
name mean sd
d_calc 0.4640788 1.8999701
d_var_calc 0.2453866 0.5513378
mean_age 915.2242476 338.2881220
n_1 15.4095238 5.9738134
sd_1 0.1312320 0.0846320
x_1 0.5557925 0.1121752

Categorical Variables

CATEGORICAL_VARS <- c("sentence_structure", "agent_argument_type", "patient_argument_type", "stimuli_actor",
                     "presentation_type", "character_identification",
                     "test_mass_or_distributed", "practice_phase", "test_method")

long_categorical <- ma_data %>%
  pivot_longer(cols = CATEGORICAL_VARS) %>%
  count(name, value) # this is a short cut for group_by() %>% summarize(count = n()) 

long_categorical %>%
  ggplot(aes(x = value, y = n)) +  
  facet_wrap(~ name, scale = "free_x") +
  geom_col(position = 'dodge',width=0.4) + 
  theme(text = element_text(size=8),
        axis.text.x = element_text(angle = 90, hjust = 1))  # rotate x-axis text

Explore Moderators

no moderators

all

m1 <- rma.mv(d_calc, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m1)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -293.3322   586.6645   590.6645   595.9533   590.7833   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3820  0.6180     30     no  short_cite 
## 
## Test for Heterogeneity:
## Q(df = 104) = 783.8714, p-val < .0001
## 
## Model Results:
## 
## estimate      se    zval    pval   ci.lb   ci.ub 
##   0.4296  0.1183  3.6319  0.0003  0.1978  0.6615  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

<36

ma_data_young <- ma_data %>%
    mutate(age_months = mean_age/30.44) %>% 
    filter(age_months < 36) 

m_young <- rma.mv(d_calc, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young)
summary(m_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -202.6954   405.3909   409.3909   414.0258   409.5575   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4618  0.6796     23     no  short_cite 
## 
## Test for Heterogeneity:
## Q(df = 75) = 570.7198, p-val < .0001
## 
## Model Results:
## 
## estimate      se    zval    pval   ci.lb   ci.ub 
##   0.3755  0.1479  2.5391  0.0111  0.0856  0.6654  * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36

ma_data_old <- ma_data %>%
    mutate(age_months = mean_age/30.44) %>% 
    filter(age_months > 36 | age_months == 36) 

m_old <- rma.mv(d_calc, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -85.8581  171.7162  175.7162  178.3806  176.1962   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.1764  0.4200      8     no  short_cite 
## 
## Test for Heterogeneity:
## Q(df = 28) = 206.4380, p-val < .0001
## 
## Model Results:
## 
## estimate      se    zval    pval   ci.lb   ci.ub 
##   0.6237  0.1650  3.7796  0.0002  0.3003  0.9472  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

age only

colored by unique_id

ma_data %>% 
  ggplot(aes(x = mean_age/30.44, y = d_calc,color = unique_id)) +
  geom_point() +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (months)") 

all

ma_data %>% 
  ggplot(aes(x = mean_age/30.44, y = d_calc, size = n_1)) +
  geom_point() +
  geom_smooth(method = "lm") +
  geom_smooth(color = "red") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (months)") +
  theme(legend.position = "none") 

m_age <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -291.7567   583.5134   589.5134   597.4176   589.7558   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3869  0.6220     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 103) = 782.2682, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.7089, p-val = 0.1911
## 
## Model Results:
## 
##           estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt     0.1455  0.2479  0.5868  0.5573  -0.3404  0.6313    
## mean_age    0.0003  0.0002  1.3073  0.1911  -0.0002  0.0008    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
forest(m_age,
       header = T,
       slab = ma_data$unique_id,
       col = "red",
       cex = .7
)

funnel(m_age)

young, < 36

ma_data_young %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1)) +
  geom_point() +
  geom_smooth(method = "lm") +
  geom_smooth(color = "red") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") +
  theme(legend.position = "none") 

m_age_young <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young)
summary(m_age_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -201.6933   403.3866   409.3866   416.2988   409.7295   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4673  0.6836     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 74) = 560.5676, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0680, p-val = 0.7943
## 
## Model Results:
## 
##           estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt     0.5537  0.6991   0.7919  0.4284  -0.8166  1.9239    
## mean_age   -0.0002  0.0009  -0.2607  0.7943  -0.0020  0.0015    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
forest(m_age_young,
       header = T,
       slab = ma_data_young$unique_id,
       col = "red",
       cex = .7
)

old, >= 36

ma_data_old %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1)) +
  geom_point() +
  geom_smooth(method = "lm") +
  geom_smooth(color = "red") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") +
  theme(legend.position = "none") 

m_age_old <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -85.8085  171.6171  177.6171  181.5046  178.6606   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.1832  0.4280      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 27) = 206.4378, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.5825, p-val = 0.4453
## 
## Model Results:
## 
##           estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt     0.3282  0.4232  0.7755  0.4381  -0.5013  1.1578    
## mean_age    0.0002  0.0003  0.7632  0.4453  -0.0003  0.0008    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

age and test type

all

ma_data %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_method)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown my method") 

m_age_method <- rma.mv(d_calc ~ mean_age + test_method, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_method)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -290.9599   581.9197   589.9197   600.4196   590.3321   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3986  0.6313     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 780.7486, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.8068, p-val = 0.4052
## 
## Model Results:
## 
##                   estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt             0.1492  0.2499  0.5969  0.5505  -0.3407  0.6391    
## mean_age            0.0003  0.0003  1.0728  0.2834  -0.0002  0.0008    
## test_methodpoint    0.0926  0.2963  0.3126  0.7545  -0.4881  0.6733    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

age and sentence structure

all

ma_data %>% 
  filter(sentence_structure != "bare_verb") %>%
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, , color = sentence_structure)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") 

m_age_sentence <- rma.mv(d_calc ~ mean_age + sentence_structure, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_sentence)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -277.1705   554.3411   562.3411   572.8410   562.7534   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4433  0.6658     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 774.2955, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 31.1505, p-val < .0001
## 
## Model Results:
## 
##                               estimate      se     zval    pval    ci.lb 
## intrcpt                        -0.1059  0.2592  -0.4085  0.6829  -0.6139 
## mean_age                        0.0003  0.0002   1.1396  0.2545  -0.0002 
## sentence_structuretransitive    0.4331  0.0798   5.4259  <.0001   0.2767 
##                                ci.ub 
## intrcpt                       0.4022      
## mean_age                      0.0008      
## sentence_structuretransitive  0.5895  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Interaction:

m_age_sentence <- rma.mv(d_calc ~ mean_age * sentence_structure, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_sentence)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -272.2966   544.5932   554.5932   567.6688   555.2248   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4384  0.6621     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 101) = 761.9948, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 41.2039, p-val < .0001
## 
## Model Results:
## 
##                                        estimate      se     zval    pval 
## intrcpt                                  0.4127  0.3057   1.3498  0.1771 
## mean_age                                -0.0003  0.0003  -1.0311  0.3025 
## sentence_structuretransitive            -0.2296  0.2233  -1.0283  0.3038 
## mean_age:sentence_structuretransitive    0.0007  0.0002   3.1759  0.0015 
##                                          ci.lb   ci.ub 
## intrcpt                                -0.1865  1.0119     
## mean_age                               -0.0009  0.0003     
## sentence_structuretransitive           -0.6673  0.2081     
## mean_age:sentence_structuretransitive   0.0003  0.0012  ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

< 36, young

ma_data_young_only <- ma_data %>%
    mutate(age_months = mean_age/30.44) %>% 
    filter(age_months < 36) 

ma_data_young_only %>% 
  filter(sentence_structure != "bare_verb") %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, , color = sentence_structure)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") 

m_age_sentence_young <- rma.mv(d_calc ~ mean_age + sentence_structure, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_sentence_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -197.4238   394.8475   402.8475   412.0094   403.4358   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.5015  0.7082     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 73) = 559.5013, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 8.6658, p-val = 0.0131
## 
## Model Results:
## 
##                               estimate      se     zval    pval    ci.lb 
## intrcpt                         0.5518  0.7102   0.7769  0.4372  -0.8402 
## mean_age                       -0.0004  0.0009  -0.4967  0.6194  -0.0022 
## sentence_structuretransitive    0.2688  0.0916   2.9347  0.0033   0.0893 
##                                ci.ub 
## intrcpt                       1.9438     
## mean_age                      0.0013     
## sentence_structuretransitive  0.4483  ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

interaction:

m_age_sentence_young <- rma.mv(d_calc ~ mean_age * sentence_structure, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_sentence_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -196.9600   393.9201   403.9201   415.3034   404.8292   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4942  0.7030     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 72) = 554.1432, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 9.7799, p-val = 0.0205
## 
## Model Results:
## 
##                                        estimate      se     zval    pval 
## intrcpt                                  0.2327  0.7701   0.3022  0.7625 
## mean_age                                -0.0000  0.0010  -0.0063  0.9949 
## sentence_structuretransitive             0.7498  0.4622   1.6221  0.1048 
## mean_age:sentence_structuretransitive   -0.0007  0.0006  -1.0624  0.2881 
##                                          ci.lb   ci.ub 
## intrcpt                                -1.2766  1.7421    
## mean_age                               -0.0019  0.0019    
## sentence_structuretransitive           -0.1562  1.6557    
## mean_age:sentence_structuretransitive  -0.0019  0.0006    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36, old

ma_data_old <- ma_data %>%
    mutate(age_months = mean_age/30.44) %>% 
    filter(age_months > 36 | age_months == 36) 

ma_data_old %>% 
  filter(sentence_structure != "bare_verb") %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = sentence_structure)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") 

m_age_sentence_old <- rma.mv(d_calc ~ mean_age + sentence_structure, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_sentence_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -68.8315  137.6630  145.6630  150.6954  147.5678   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.2999  0.5476      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 26) = 187.4101, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 35.2659, p-val < .0001
## 
## Model Results:
## 
##                               estimate      se     zval    pval    ci.lb 
## intrcpt                        -0.4355  0.4625  -0.9416  0.3464  -1.3421 
## mean_age                        0.0003  0.0003   0.9103  0.3627  -0.0003 
## sentence_structuretransitive    0.9653  0.1640   5.8854  <.0001   0.6438 
##                                ci.ub 
## intrcpt                       0.4711      
## mean_age                      0.0008      
## sentence_structuretransitive  1.2868  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

interaction

m_age_sentence_old <- rma.mv(d_calc ~ mean_age * sentence_structure, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_sentence_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -68.7597  137.5194  147.5194  153.6137  150.6773   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.2660  0.5158      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 25) = 175.6807, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 35.5003, p-val < .0001
## 
## Model Results:
## 
##                                        estimate      se     zval    pval 
## intrcpt                                  0.3053  1.1491   0.2657  0.7905 
## mean_age                                -0.0003  0.0008  -0.3182  0.7503 
## sentence_structuretransitive             0.1055  1.2385   0.0852  0.9321 
## mean_age:sentence_structuretransitive    0.0006  0.0009   0.6936  0.4879 
##                                          ci.lb   ci.ub 
## intrcpt                                -1.9469  2.5576    
## mean_age                               -0.0018  0.0013    
## sentence_structuretransitive           -2.3219  2.5329    
## mean_age:sentence_structuretransitive  -0.0011  0.0023    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

age with stimuli_actor

all

ma_data %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = stimuli_actor)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by stimuli_actor") 

m_age_stimuli_actor <- rma.mv(d_calc ~ mean_age + stimuli_actor, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
m_age_stimuli_actor_interaction <- rma.mv(d_calc ~ mean_age * stimuli_actor, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_stimuli_actor)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -290.5855   581.1710   589.1710   599.6709   589.5834   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3828  0.6187     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 764.8432, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 2.0931, p-val = 0.3511
## 
## Model Results:
## 
##                      estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                0.2385  0.2890   0.8253  0.4092  -0.3279  0.8050    
## mean_age               0.0003  0.0002   1.2576  0.2085  -0.0002  0.0008    
## stimuli_actorperson   -0.1369  0.2208  -0.6198  0.5354  -0.5696  0.2959    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_stimuli_actor_interaction)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -288.4297   576.8595   586.8595   599.9351   587.4911   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4382  0.6620     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 101) = 764.4812, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 5.1449, p-val = 0.1615
## 
## Model Results:
## 
##                               estimate      se     zval    pval    ci.lb 
## intrcpt                         0.5501  0.3512   1.5664  0.1173  -0.1382 
## mean_age                       -0.0001  0.0003  -0.1968  0.8439  -0.0007 
## stimuli_actorperson            -0.8697  0.4810  -1.8081  0.0706  -1.8124 
## mean_age:stimuli_actorperson    0.0009  0.0005   1.7805  0.0750  -0.0001 
##                                ci.ub 
## intrcpt                       1.2385    
## mean_age                      0.0006    
## stimuli_actorperson           0.0731  . 
## mean_age:stimuli_actorperson  0.0018  . 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

<36, young

ma_data_young_only %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = stimuli_actor)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by stimuli_actor, young only") 

m_age_stimuli_actor_young <- rma.mv(d_calc ~ mean_age + stimuli_actor, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_stimuli_actor_interaction_young <- rma.mv(d_calc ~ mean_age * stimuli_actor, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_stimuli_actor_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -200.7159   401.4317   409.4317   418.5935   410.0199   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4793  0.6923     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 73) = 552.6059, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.0974, p-val = 0.9525
## 
## Model Results:
## 
##                      estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                0.5818  0.7268   0.8005  0.4234  -0.8427  2.0064    
## mean_age              -0.0002  0.0009  -0.2513  0.8016  -0.0020  0.0015    
## stimuli_actorperson   -0.0507  0.2715  -0.1868  0.8518  -0.5828  0.4814    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_stimuli_actor_interaction_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -199.6775   399.3549   409.3549   420.7383   410.2640   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.5075  0.7124     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 72) = 544.9146, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 0.2277, p-val = 0.9730
## 
## Model Results:
## 
##                               estimate      se     zval    pval    ci.lb 
## intrcpt                         0.8661  1.0700   0.8095  0.4182  -1.2310 
## mean_age                       -0.0006  0.0014  -0.4462  0.6554  -0.0034 
## stimuli_actorperson            -0.5866  1.4191  -0.4134  0.6793  -3.3681 
## mean_age:stimuli_actorperson    0.0007  0.0019   0.3909  0.6959  -0.0029 
##                                ci.ub 
## intrcpt                       2.9632    
## mean_age                      0.0021    
## stimuli_actorperson           2.1949    
## mean_age:stimuli_actorperson  0.0044    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36, old

ma_data_old %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = stimuli_actor)) +
  geom_point() +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by stimuli_actor, old only") 

m_age_stimuli_actor_old <- rma.mv(d_calc ~ mean_age + stimuli_actor, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
m_age_stimuli_actor_interaction_old <- rma.mv(d_calc ~ mean_age * stimuli_actor, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_stimuli_actor_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -84.8371  169.6742  177.6742  182.7066  179.5790   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.1992  0.4463      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 26) = 204.0420, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.9935, p-val = 0.6085
## 
## Model Results:
## 
##                      estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                0.4278  0.4545   0.9412  0.3466  -0.4631  1.3186    
## mean_age               0.0002  0.0003   0.7776  0.4368  -0.0003  0.0008    
## stimuli_actorperson   -0.2209  0.3482  -0.6345  0.5258  -0.9033  0.4615    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_stimuli_actor_interaction_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -83.5148  167.0297  177.0297  183.1240  180.1876   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.2964  0.5444      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 25) = 204.0071, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 4.2728, p-val = 0.2335
## 
## Model Results:
## 
##                               estimate      se     zval    pval    ci.lb 
## intrcpt                         0.9892  0.5728   1.7269  0.0842  -0.1335 
## mean_age                       -0.0002  0.0004  -0.5140  0.6073  -0.0009 
## stimuli_actorperson            -1.6965  0.9084  -1.8676  0.0618  -3.4769 
## mean_age:stimuli_actorperson    0.0011  0.0006   1.8439  0.0652  -0.0001 
##                                ci.ub 
## intrcpt                       2.1119  . 
## mean_age                      0.0005    
## stimuli_actorperson           0.0839  . 
## mean_age:stimuli_actorperson  0.0023  . 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

age with presentation_type

Decided to only compare asynchronous and immediate after:

ma_data %>% 
  count(presentation_type)
## # A tibble: 3 x 2
##   presentation_type     n
##   <chr>             <int>
## 1 asynchronous         37
## 2 immediate_after      49
## 3 simultaneous         19
ma_data_pt <- ma_data %>% 
  filter(presentation_type != "simultaneous") 

ma_data_pt_young <- ma_data_pt %>% 
  mutate(age_months = mean_age/30.44) %>% 
    filter(age_months < 36) 


ma_data_pt_old <- ma_data_pt %>% 
  mutate(age_months = mean_age/30.44) %>% 
    filter(age_months > 36 | age_months == 36) 

all

ma_data_pt %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1,  color = presentation_type)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by presentation type") 

m_age_pt <- rma.mv(d_calc ~ mean_age + presentation_type, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_pt)

m_age_pt_interaction <- rma.mv(d_calc ~ mean_age * presentation_type, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_pt)

summary(m_age_pt)
## 
## Multivariate Meta-Analysis Model (k = 86; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -215.4681   430.9363   438.9363   448.6116   439.4491   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4775  0.6910     20     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 83) = 579.8795, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.1224, p-val = 0.9406
## 
## Model Results:
## 
##                                   estimate      se    zval    pval    ci.lb 
## intrcpt                             0.4895  0.3154  1.5522  0.1206  -0.1286 
## mean_age                            0.0000  0.0003  0.0413  0.9671  -0.0006 
## presentation_typeimmediate_after    0.0630  0.1887  0.3338  0.7385  -0.3068 
##                                    ci.ub 
## intrcpt                           1.1077    
## mean_age                          0.0006    
## presentation_typeimmediate_after  0.4327    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_pt_interaction)
## 
## Multivariate Meta-Analysis Model (k = 86; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -214.0267   428.0533   438.0533   450.0869   438.8428   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4624  0.6800     20     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 82) = 571.1112, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 1.2903, p-val = 0.7314
## 
## Model Results:
## 
##                                            estimate      se     zval    pval 
## intrcpt                                      1.3121  0.8299   1.5809  0.1139 
## mean_age                                    -0.0012  0.0012  -1.0205  0.3075 
## presentation_typeimmediate_after            -0.7348  0.7704  -0.9539  0.3401 
## mean_age:presentation_typeimmediate_after    0.0012  0.0012   1.0731  0.2832 
##                                              ci.lb   ci.ub 
## intrcpt                                    -0.3146  2.9387    
## mean_age                                   -0.0034  0.0011    
## presentation_typeimmediate_after           -2.2447  0.7750    
## mean_age:presentation_typeimmediate_after  -0.0010  0.0035    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

<36, young

ma_data_pt_young %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1,  color = presentation_type)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by presentation type, young only") 

m_data_pt_young <- rma.mv(d_calc ~ mean_age + presentation_type, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_pt_young)

m_age_pt_interaction_young <- rma.mv(d_calc ~ mean_age * presentation_type, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_pt_young)

summary(m_age_pt)
## 
## Multivariate Meta-Analysis Model (k = 86; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -215.4681   430.9363   438.9363   448.6116   439.4491   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4775  0.6910     20     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 83) = 579.8795, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.1224, p-val = 0.9406
## 
## Model Results:
## 
##                                   estimate      se    zval    pval    ci.lb 
## intrcpt                             0.4895  0.3154  1.5522  0.1206  -0.1286 
## mean_age                            0.0000  0.0003  0.0413  0.9671  -0.0006 
## presentation_typeimmediate_after    0.0630  0.1887  0.3338  0.7385  -0.3068 
##                                    ci.ub 
## intrcpt                           1.1077    
## mean_age                          0.0006    
## presentation_typeimmediate_after  0.4327    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_pt_interaction)
## 
## Multivariate Meta-Analysis Model (k = 86; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -214.0267   428.0533   438.0533   450.0869   438.8428   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4624  0.6800     20     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 82) = 571.1112, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 1.2903, p-val = 0.7314
## 
## Model Results:
## 
##                                            estimate      se     zval    pval 
## intrcpt                                      1.3121  0.8299   1.5809  0.1139 
## mean_age                                    -0.0012  0.0012  -1.0205  0.3075 
## presentation_typeimmediate_after            -0.7348  0.7704  -0.9539  0.3401 
## mean_age:presentation_typeimmediate_after    0.0012  0.0012   1.0731  0.2832 
##                                              ci.lb   ci.ub 
## intrcpt                                    -0.3146  2.9387    
## mean_age                                   -0.0034  0.0011    
## presentation_typeimmediate_after           -2.2447  0.7750    
## mean_age:presentation_typeimmediate_after  -0.0010  0.0035    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36, old

ma_data_pt_old %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1,  color = presentation_type)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by presentation type, young only") 

age with character_identification

all

ma_data %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = character_identification)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by character_identification") 

m_age_ci <- rma.mv(d_calc ~ mean_age + character_identification, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
m_age_stimuli_ci_interaction <- rma.mv(d_calc ~ mean_age * character_identification, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_ci)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -288.4414   576.8829   584.8829   595.3827   585.2952   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3801  0.6165     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 767.9935, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 6.6790, p-val = 0.0355
## 
## Model Results:
## 
##                              estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                        0.0022  0.2552  0.0087  0.9930  -0.4980  0.5025 
## mean_age                       0.0002  0.0002  0.9841  0.3251  -0.0002  0.0007 
## character_identificationyes    0.4330  0.1942  2.2294  0.0258   0.0523  0.8137 
##  
## intrcpt 
## mean_age 
## character_identificationyes  * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_stimuli_ci_interaction)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -284.7699   569.5398   579.5398   592.6154   580.1714   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3935  0.6273     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 101) = 767.2829, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 12.7724, p-val = 0.0052
## 
## Model Results:
## 
##                                       estimate      se     zval    pval 
## intrcpt                                -0.5587  0.3420  -1.6338  0.1023 
## mean_age                                0.0010  0.0004   2.5379  0.0112 
## character_identificationyes             1.4183  0.4428   3.2033  0.0014 
## mean_age:character_identificationyes   -0.0012  0.0005  -2.4751  0.0133 
##                                         ci.lb    ci.ub 
## intrcpt                               -1.2289   0.1115     
## mean_age                               0.0002   0.0017   * 
## character_identificationyes            0.5505   2.2861  ** 
## mean_age:character_identificationyes  -0.0021  -0.0002   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

<36, young

ma_data_young_only %>% 
  mutate(age_months = mean_age/30.44) %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = character_identification)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by character_identification, young only") 

m_age_ci_young <- rma.mv(d_calc ~ mean_age + character_identification, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_ci_interaction_young <- rma.mv(d_calc ~ mean_age * character_identification, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_ci_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -197.9216   395.8431   403.8431   413.0050   404.4314   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4376  0.6616     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 73) = 531.1789, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 6.0267, p-val = 0.0491
## 
## Model Results:
## 
##                              estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                        0.5679  0.6887   0.8246  0.4096  -0.7820  1.9178 
## mean_age                      -0.0005  0.0009  -0.6155  0.5382  -0.0023  0.0012 
## character_identificationyes    0.5386  0.2209   2.4379  0.0148   0.1056  0.9717 
##  
## intrcpt 
## mean_age 
## character_identificationyes  * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_ci_interaction_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -197.0208   394.0417   404.0417   415.4250   404.9507   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4322  0.6574     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 72) = 524.7532, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 6.2314, p-val = 0.1009
## 
## Model Results:
## 
##                                       estimate      se     zval    pval 
## intrcpt                                 0.3388  0.8795   0.3852  0.7001 
## mean_age                               -0.0002  0.0012  -0.1884  0.8506 
## character_identificationyes             1.0724  1.2756   0.8406  0.4005 
## mean_age:character_identificationyes   -0.0007  0.0017  -0.4253  0.6706 
##                                         ci.lb   ci.ub 
## intrcpt                               -1.3849  2.0625    
## mean_age                              -0.0025  0.0021    
## character_identificationyes           -1.4278  3.5725    
## mean_age:character_identificationyes  -0.0040  0.0026    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36, old

ma_data_old %>% 
  mutate(age_months = mean_age/30.44) %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = character_identification)) +
  geom_point() +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by character_identification, old only") 

age with practice_phase

all

ma_data %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = practice_phase)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by practice_phase") 

m_age_pf <- rma.mv(d_calc ~ mean_age + character_identification, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
m_age_pf_interaction <- rma.mv(d_calc ~ mean_age * character_identification, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_ci)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -288.4414   576.8829   584.8829   595.3827   585.2952   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3801  0.6165     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 767.9935, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 6.6790, p-val = 0.0355
## 
## Model Results:
## 
##                              estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                        0.0022  0.2552  0.0087  0.9930  -0.4980  0.5025 
## mean_age                       0.0002  0.0002  0.9841  0.3251  -0.0002  0.0007 
## character_identificationyes    0.4330  0.1942  2.2294  0.0258   0.0523  0.8137 
##  
## intrcpt 
## mean_age 
## character_identificationyes  * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_stimuli_ci_interaction)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -284.7699   569.5398   579.5398   592.6154   580.1714   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3935  0.6273     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 101) = 767.2829, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 12.7724, p-val = 0.0052
## 
## Model Results:
## 
##                                       estimate      se     zval    pval 
## intrcpt                                -0.5587  0.3420  -1.6338  0.1023 
## mean_age                                0.0010  0.0004   2.5379  0.0112 
## character_identificationyes             1.4183  0.4428   3.2033  0.0014 
## mean_age:character_identificationyes   -0.0012  0.0005  -2.4751  0.0133 
##                                         ci.lb    ci.ub 
## intrcpt                               -1.2289   0.1115     
## mean_age                               0.0002   0.0017   * 
## character_identificationyes            0.5505   2.2861  ** 
## mean_age:character_identificationyes  -0.0021  -0.0002   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

<36, young

ma_data_young_only %>% 
  mutate(age_months = mean_age/30.44) %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = practice_phase)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by practice_phase, young only") 

m_age_pf_young <- rma.mv(d_calc ~ mean_age + practice_phase, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_pf_interaction_young <- rma.mv(d_calc ~ mean_age * practice_phase, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_pf_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -200.5617   401.1234   409.1234   418.2852   409.7116   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4238  0.6510     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 73) = 535.9618, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.2744, p-val = 0.5288
## 
## Model Results:
## 
##                    estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt              0.7018  0.6931   1.0126  0.3113  -0.6566  2.0603    
## mean_age            -0.0005  0.0009  -0.5842  0.5591  -0.0023  0.0012    
## practice_phaseyes    0.1817  0.1671   1.0875  0.2768  -0.1458  0.5093    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_pf_interaction_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -198.9942   397.9885   407.9885   419.3718   408.8976   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4555  0.6749     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 72) = 530.7942, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.8556, p-val = 0.4144
## 
## Model Results:
## 
##                             estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                       1.2301  0.8193   1.5014  0.1332  -0.3757  2.8359 
## mean_age                     -0.0013  0.0011  -1.1944  0.2323  -0.0035  0.0009 
## practice_phaseyes            -1.1221  0.9964  -1.1261  0.2601  -3.0751  0.8309 
## mean_age:practice_phaseyes    0.0019  0.0014   1.3181  0.1875  -0.0009  0.0047 
##  
## intrcpt 
## mean_age 
## practice_phaseyes 
## mean_age:practice_phaseyes 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36, old

ma_data_old %>% 
  mutate(age_months = mean_age/30.44) %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = practice_phase)) +
  geom_point() +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by practice_phase, old only") 

age with test_mass_or_distributed

all

ma_data %>% 
  mutate(age_months = mean_age/30.44) %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_mass_or_distributed)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by test type") 

m_age_tt <- rma.mv(d_calc ~ mean_age + test_mass_or_distributed, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
m_age_tt_interaction <- rma.mv(d_calc ~ mean_age * test_mass_or_distributed, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_age_tt)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -290.1523   580.3047   588.3047   598.8046   588.7170   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3870  0.6221     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 769.1828, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 2.7628, p-val = 0.2512
## 
## Model Results:
## 
##                               estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                         0.0394  0.2686  0.1466  0.8834  -0.4870  0.5658 
## mean_age                        0.0003  0.0002  1.4389  0.1502  -0.0001  0.0008 
## test_mass_or_distributedmass    0.2793  0.2720  1.0266  0.3046  -0.2539  0.8124 
##  
## intrcpt 
## mean_age 
## test_mass_or_distributedmass 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_tt_interaction)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -288.1692   576.3383   586.3383   599.4139   586.9699   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3734  0.6111     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 101) = 755.6914, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 5.0953, p-val = 0.1649
## 
## Model Results:
## 
##                                        estimate      se     zval    pval 
## intrcpt                                 -0.0811  0.2782  -0.2915  0.7707 
## mean_age                                 0.0005  0.0003   1.8617  0.0626 
## test_mass_or_distributedmass             1.2284  0.6808   1.8043  0.0712 
## mean_age:test_mass_or_distributedmass   -0.0012  0.0008  -1.5166  0.1294 
##                                          ci.lb   ci.ub 
## intrcpt                                -0.6263  0.4641    
## mean_age                               -0.0000  0.0010  . 
## test_mass_or_distributedmass           -0.1060  2.5629  . 
## mean_age:test_mass_or_distributedmass  -0.0027  0.0003    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

<36, young

ma_data_young_only %>% 
  mutate(age_months = mean_age/30.44) %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_mass_or_distributed)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by test_mass_or_distributed, young only") 

m_age_tt_young <- rma.mv(d_calc ~ mean_age + test_mass_or_distributed, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_tt_interaction_young <- rma.mv(d_calc ~ mean_age * test_mass_or_distributed, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_tt_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -199.7548   399.5096   407.5096   416.6715   408.0979   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4574  0.6763     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 73) = 548.4824, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.6835, p-val = 0.4310
## 
## Model Results:
## 
##                               estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                         0.1770  0.7580  0.2335  0.8154  -1.3087  1.6627 
## mean_age                        0.0001  0.0009  0.0979  0.9221  -0.0017  0.0019 
## test_mass_or_distributedmass    0.4228  0.3331  1.2692  0.2044  -0.2301  1.0757 
##  
## intrcpt 
## mean_age 
## test_mass_or_distributedmass 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_age_tt_interaction_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -198.4770   396.9539   406.9539   418.3373   407.8630   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4784  0.6917     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 72) = 548.4171, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.4680, p-val = 0.4811
## 
## Model Results:
## 
##                                        estimate      se     zval    pval 
## intrcpt                                 -0.5423  1.0886  -0.4982  0.6184 
## mean_age                                 0.0010  0.0013   0.7375  0.4608 
## test_mass_or_distributedmass             1.7117  1.4382   1.1901  0.2340 
## mean_age:test_mass_or_distributedmass   -0.0017  0.0019  -0.9216  0.3567 
##                                          ci.lb   ci.ub 
## intrcpt                                -2.6759  1.5913    
## mean_age                               -0.0016  0.0036    
## test_mass_or_distributedmass           -1.1072  4.5305    
## mean_age:test_mass_or_distributedmass  -0.0053  0.0019    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

>= 36, old

ma_data_old %>% 
  mutate(age_months = mean_age/30.44) %>%
  ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_mass_or_distributed)) +
  geom_point() +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by test_mass_or_distributed, old only") 

repetition only

repetition only

ma_data %>% 
  ggplot(mapping = aes(x = n_repetitions_sentence, y = d_calc)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("number of repetition per novel verb") +
  ggtitle("Syntactical Bootstrapping effect size vs. number of repetitions for verb") +
  theme_classic() +
  theme(legend.position = "none")

m_rep <- rma.mv(d_calc ~ n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_rep)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -292.6018   585.2036   591.2036   599.1078   591.4460   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3900  0.6245     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 103) = 782.9687, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0174, p-val = 0.8949
## 
## Model Results:
## 
##                         estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                   0.4162  0.1574  2.6436  0.0082   0.1076  0.7248  ** 
## n_repetitions_sentence    0.0018  0.0137  0.1321  0.8949  -0.0251  0.0287     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

repetition only, young

ma_data_young %>% 
  ggplot(mapping = aes(x = n_repetitions_sentence, y = d_calc)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("number of repetition per novel verb") +
  ggtitle("Syntactical Bootstrapping effect size vs. number of repetitions for verb") +
  theme_classic() +
  theme(legend.position = "none")

m_rep_young <- rma.mv(d_calc ~ n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young)
summary(m_rep_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -201.9811   403.9621   409.9621   416.8743   410.3050   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4736  0.6882     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 74) = 570.5964, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1498, p-val = 0.6987
## 
## Model Results:
## 
##                         estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                   0.3249  0.1990  1.6329  0.1025  -0.0651  0.7149    
## n_repetitions_sentence    0.0057  0.0148  0.3870  0.6987  -0.0232  0.0347    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

repetition only, old

ma_data_old %>% 
  ggplot(mapping = aes(x = n_repetitions_sentence, y = d_calc)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("number of repetition per novel verb") +
  ggtitle("Syntactical Bootstrapping effect size vs. number of repetitions for verb") +
  theme_classic() +
  theme(legend.position = "none")

m_rep_old <- rma.mv(d_calc ~ n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_rep_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -84.5965  169.1930  175.1930  179.0805  176.2365   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.1846  0.4297      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 27) = 205.4444, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.9520, p-val = 0.3292
## 
## Model Results:
## 
##                         estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                   0.3077  0.3662  0.8402  0.4008  -0.4100  1.0254    
## n_repetitions_sentence    0.0929  0.0952  0.9757  0.3292  -0.0937  0.2796    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

repetition with age

correlation

all

m_rep_age <- rma.mv(d_calc ~ mean_age + n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
m_rep_age_interaction <- rma.mv(d_calc ~ mean_age*n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data)
summary(m_rep_age)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -291.0774   582.1548   590.1548   600.6547   590.5671   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3973  0.6303     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 102) = 782.1754, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.9251, p-val = 0.3819
## 
## Model Results:
## 
##                         estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                   0.0703  0.2961  0.2373  0.8124  -0.5101  0.6506    
## mean_age                  0.0003  0.0002  1.3805  0.1674  -0.0001  0.0008    
## n_repetitions_sentence    0.0066  0.0142  0.4649  0.6420  -0.0212  0.0343    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_rep_age_interaction)
## 
## Multivariate Meta-Analysis Model (k = 105; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -290.1825   580.3649   590.3649   603.4405   590.9965   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.3964  0.6296     30     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 101) = 774.7436, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.1813, p-val = 0.5356
## 
## Model Results:
## 
##                                  estimate      se     zval    pval    ci.lb 
## intrcpt                            0.0025  0.3250   0.0077  0.9939  -0.6344 
## mean_age                           0.0005  0.0004   1.3224  0.1860  -0.0002 
## n_repetitions_sentence             0.0305  0.0493   0.6188  0.5361  -0.0661 
## mean_age:n_repetitions_sentence   -0.0000  0.0001  -0.5067  0.6124  -0.0002 
##                                   ci.ub 
## intrcpt                          0.6394    
## mean_age                         0.0012    
## n_repetitions_sentence           0.1270    
## mean_age:n_repetitions_sentence  0.0001    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

young, <36

m_rep_age_young <- rma.mv(d_calc ~ mean_age + n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young)
m_rep_age_interaction_young <- rma.mv(d_calc ~ mean_age*n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_young)
summary(m_rep_age_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -200.9924   401.9848   409.9848   419.1467   410.5731   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4840  0.6957     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 73) = 559.8183, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.1628, p-val = 0.9218
## 
## Model Results:
## 
##                         estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                   0.4037  0.8317   0.4854  0.6274  -1.2264  2.0338    
## mean_age                 -0.0001  0.0010  -0.0984  0.9216  -0.0020  0.0018    
## n_repetitions_sentence    0.0052  0.0161   0.3199  0.7490  -0.0265  0.0368    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_rep_age_interaction_young)
## 
## Multivariate Meta-Analysis Model (k = 76; method: REML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -199.8017   399.6033   409.6033   420.9867   410.5124   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.4986  0.7061     23     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 72) = 559.6199, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 1.3065, p-val = 0.7276
## 
## Model Results:
## 
##                                  estimate      se     zval    pval    ci.lb 
## intrcpt                           -0.4403  1.1428  -0.3853  0.7000  -2.6802 
## mean_age                           0.0011  0.0015   0.7530  0.4514  -0.0018 
## n_repetitions_sentence             0.0811  0.0727   1.1157  0.2646  -0.0614 
## mean_age:n_repetitions_sentence   -0.0001  0.0001  -1.0687  0.2852  -0.0003 
##                                   ci.ub 
## intrcpt                          1.7995    
## mean_age                         0.0040    
## n_repetitions_sentence           0.2236    
## mean_age:n_repetitions_sentence  0.0001    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

old > 36

m_rep_age_old <- rma.mv(d_calc ~ mean_age + n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
m_rep_age_interaction_old <- rma.mv(d_calc ~ mean_age*n_repetitions_sentence , V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_old)
summary(m_rep_age_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -84.5529  169.1058  177.1058  182.1382  179.0106   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.1936  0.4400      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 26) = 205.4251, p-val < .0001
## 
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.5081, p-val = 0.4705
## 
## Model Results:
## 
##                         estimate      se    zval    pval    ci.lb   ci.ub 
## intrcpt                   0.0145  0.5364  0.0270  0.9785  -1.0369  1.0658    
## mean_age                  0.0002  0.0003  0.7578  0.4486  -0.0003  0.0008    
## n_repetitions_sentence    0.0926  0.0966  0.9592  0.3375  -0.0966  0.2819    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(m_rep_age_interaction_old)
## 
## Multivariate Meta-Analysis Model (k = 29; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -83.4154  166.8308  176.8308  182.9252  179.9887   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.2205  0.4695      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 25) = 198.5403, p-val < .0001
## 
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.2824, p-val = 0.5159
## 
## Model Results:
## 
##                                  estimate      se     zval    pval    ci.lb 
## intrcpt                            4.2809  4.7873   0.8942  0.3712  -5.1019 
## mean_age                          -0.0034  0.0041  -0.8415  0.4001  -0.0114 
## n_repetitions_sentence            -1.3422  1.6008  -0.8384  0.4018  -4.4798 
## mean_age:n_repetitions_sentence    0.0012  0.0013   0.8988  0.3688  -0.0014 
##                                    ci.ub 
## intrcpt                          13.6638    
## mean_age                          0.0045    
## n_repetitions_sentence            1.7954    
## mean_age:n_repetitions_sentence   0.0038    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

vocab

vocab (median)

ma_data_with_vocab <- ma_data %>% 
  mutate(vocab = case_when(!is.na(productive_vocab_median) ~ productive_vocab_median,
                           !is.na(productive_vocab_mean) ~ productive_vocab_mean,
                            TRUE ~ NA_real_),
         vocab_source = case_when(!is.na(productive_vocab_median) ~ "median",
                           !is.na(productive_vocab_mean) ~ "mean",
                            TRUE ~ NA_character_)) 

ma_data_with_vocab %>%
  ggplot(aes(x = productive_vocab_median, y = d_calc)) +
  geom_point() +
  geom_smooth(method = "lm") +
  theme_classic()

m_vocab <- rma.mv(d_calc ~ productive_vocab_median, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_with_vocab)
summary(m_vocab)
## 
## Multivariate Meta-Analysis Model (k = 40; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -90.7783  181.5566  187.5566  192.4694  188.2625   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.7075  0.8412      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.3051, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0401, p-val = 0.8413
## 
## Model Results:
## 
##                          estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                    0.7831  0.4339   1.8050  0.0711  -0.0672  1.6335  . 
## productive_vocab_median   -0.0014  0.0068  -0.2003  0.8413  -0.0148  0.0120    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

age comparison

ma_data_with_vocab_age <- ma_data_with_vocab %>% 
  filter(vocab_source == "median" &
        !is.na(vocab)) 

ma_data_with_vocab_age %>% 
  ggplot(aes(x = mean_age, y = d_calc)) +
  geom_point() +
  geom_smooth(method = "lm") +
  theme_classic()

m_age_with_vocab <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_with_vocab_age)
summary(m_age_with_vocab)
## 
## Multivariate Meta-Analysis Model (k = 40; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -90.4576  180.9152  186.9152  191.8279  187.6211   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.7145  0.8453      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.4185, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3462, p-val = 0.5563
## 
## Model Results:
## 
##           estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt     1.2707  0.9825   1.2933  0.1959  -0.6550  3.1964    
## mean_age   -0.0008  0.0013  -0.5884  0.5563  -0.0034  0.0018    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

< 36, young

ma_data_with_vocab_age_young <- ma_data_with_vocab_age %>% 
  mutate(age_months = mean_age/30.44) %>% 
  filter(age_months < 36) 


ma_data_with_vocab_age_young %>% 
  ggplot(aes(x = productive_vocab_median, y = d_calc, size = n_1)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. vocab (months)") 

m_age_with_vocab_young <- rma.mv(d_calc ~ productive_vocab_median, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_with_vocab_age_young)
summary(m_age_with_vocab_young)
## 
## Multivariate Meta-Analysis Model (k = 40; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -90.7783  181.5566  187.5566  192.4694  188.2625   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.7075  0.8412      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.3051, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0401, p-val = 0.8413
## 
## Model Results:
## 
##                          estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt                    0.7831  0.4339   1.8050  0.0711  -0.0672  1.6335  . 
## productive_vocab_median   -0.0014  0.0068  -0.2003  0.8413  -0.0148  0.0120    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

< 36, young, age comparison

ma_data_with_vocab_age_young %>% 
  ggplot(aes(x = age_months, y = d_calc, size = n_1)) +
  geom_point() +
  geom_smooth(method = "lm") +
  ylab("Effect Size") +
  xlab("Age (days)") +
  ggtitle("Syntactical Bootstrapping effect size vs. Age (months)") 

m_age_with_vocab_young <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
                            random = ~ 1 | short_cite, data = ma_data_with_vocab_age_young)
summary(m_age_with_vocab)
## 
## Multivariate Meta-Analysis Model (k = 40; method: REML)
## 
##   logLik  Deviance       AIC       BIC      AICc 
## -90.4576  180.9152  186.9152  191.8279  187.6211   
## 
## Variance Components:
## 
##             estim    sqrt  nlvls  fixed      factor 
## sigma^2    0.7145  0.8453      8     no  short_cite 
## 
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.4185, p-val < .0001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3462, p-val = 0.5563
## 
## Model Results:
## 
##           estimate      se     zval    pval    ci.lb   ci.ub 
## intrcpt     1.2707  0.9825   1.2933  0.1959  -0.6550  3.1964    
## mean_age   -0.0008  0.0013  -0.5884  0.5563  -0.0034  0.0018    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

correlationt est

cor.test(ma_data_with_vocab$mean_age,
         ma_data_with_vocab$productive_vocab_median)
## 
##  Pearson's product-moment correlation
## 
## data:  ma_data_with_vocab$mean_age and ma_data_with_vocab$productive_vocab_median
## t = 12.979, df = 38, p-value = 1.532e-15
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.8235024 0.9480383
## sample estimates:
##       cor 
## 0.9032915

contingency table

ALL_CATEGORICAL_VARS <- c("test_type","presentation_type",
                      "agent_argument_type_clean", "patient_argument_type_clean", 
                     "stimuli_modality", "stimuli_actor", "character_identification", "practice_phase", "test_mass_or_distributed", "test_method")




get_cross_counts <- function(args, df){
  var1 = args[[1]]
  var2 = args[[2]]
  
  if (var1 != var2){
  
  df %>%
    select_(var1, var2) %>%
    rename(v1 = var1, 
          v2 = var2) %>%
    count(v1, v2) %>%
    mutate(v1_long = glue("{var1}/{v1}"),
           v2_long = glue("{var2}/{v2}"))  %>%
    select(v1_long, v2_long, n) 

  }
}

all_pair_counts <- list(ALL_CATEGORICAL_VARS,
                        ALL_CATEGORICAL_VARS) %>%
  cross() %>%
  map_df(get_cross_counts, ma_data) %>%
  complete(v1_long, v2_long, fill = list(n = 0)) %>%
  filter(v1_long != v2_long)


  all_counts_wide <- all_pair_counts %>%
    pivot_wider(names_from = v2_long, values_from = n) 
  

  all_counts_wide_matrix <- all_counts_wide %>%
    select(-v1_long) %>%
    as.matrix()
  
  row.names(all_counts_wide_matrix) <-   all_counts_wide$v1_long
  heatmaply(all_counts_wide_matrix,
            fontsize_row = 8,
            fontsize_col = 8)

Model selections??

http://www.metafor-project.org/doku.php/tips:model_selection_with_glmulti_and_mumin

eval(metafor:::.MuMIn)

ma_data
## # A tibble: 105 x 55
##       x1 coder unique_id link  grammatical_cla… paper_eligibili… short_cite
##    <dbl> <chr> <chr>     <chr> <chr>            <chr>            <chr>     
##  1     1 alan… arunacha… http… verb             include          Arunachal…
##  2     2 alan… arunacha… http… verb             include          Arunachal…
##  3     3 alan… arunacha… http… verb             include          Arunachal…
##  4     4 alan… arunacha… http… verb             include          Arunachal…
##  5     5 alan… arunacha… http… verb             include          Arunachal…
##  6     6 anjie arunacha… http… verb             include          Arunachal…
##  7     7 anjie arunacha… http… verb             include          Arunachal…
##  8     8 alan… bunger20… http… verb             include          Bunger, A…
##  9     9 alan… bunger20… http… verb             include          Bunger, A…
## 10    10 alan… bunger20… http… verb             include          Bunger, A…
## # … with 95 more rows, and 48 more variables: data_source <chr>,
## #   expt_num <chr>, expt_condition <chr>, dependent_measure <chr>,
## #   test_type <chr>, same_infant <chr>, language <chr>, mean_age <dbl>,
## #   productive_vocab_mean <dbl>, productive_vocab_median <dbl>,
## #   population_type <chr>, sentence_structure <chr>, agent_argument_type <chr>,
## #   patient_argument_type <chr>, verb_type <chr>, stimuli_type <chr>,
## #   stimuli_modality <chr>, stimuli_actor <chr>, presentation_type <chr>,
## #   character_identification <chr>, practice_phase <chr>,
## #   test_mass_or_distributed <chr>, n_train_test_pair <dbl>,
## #   n_test_trial_per_pair <dbl>, n_repetitions_sentence <dbl>,
## #   n_repetitions_video <dbl>, example_target_sentence <chr>,
## #   test_question <chr>, inclusion_certainty <dbl>, note <chr>, n_1 <dbl>,
## #   x_1 <dbl>, x_2 <dbl>, x_2_raw <dbl>, sd_1 <dbl>, sd_2 <dbl>,
## #   sd_2_raw <dbl>, t <dbl>, d <dbl>, d_calc <dbl>, d_var_calc <dbl>,
## #   es_method <chr>, unique_infant <chr>, test_method <chr>,
## #   agent_argument_type_clean <chr>, patient_argument_type_clean <chr>,
## #   adult_participant <chr>, data_source_clean <chr>
full <- rma.mv(d_calc, d_var_calc, mods = ~ mean_age + agent_argument_type_clean + patient_argument_type_clean + stimuli_modality + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video + test_method,
            data=ma_data, method="ML")

res <- dredge(full, trace=2)
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subset(res, delta <= 2, recalc.weights=FALSE)
## Global model call: rma.mv(yi = d_calc, V = d_var_calc, mods = ~mean_age + agent_argument_type_clean + 
##     patient_argument_type_clean + stimuli_modality + stimuli_actor + 
##     presentation_type + test_mass_or_distributed + practice_phase + 
##     character_identification + n_repetitions_sentence + n_repetitions_video + 
##     test_method, data = ma_data, method = "ML")
## ---
## Model selection table 
##      (Int) agn_arg_typ_cln chr_idn n_rpt_snt n_rpt_vid ptn_arg_typ_cln prc_phs
## 4028     +               +       +   0.02482   -0.1557               +        
## 4026     +               +           0.02037   -0.1422               +        
## 4090     +               +           0.02110   -0.1083               +       +
## 1980     +               +       +   0.02196   -0.1757               +        
##      prs_typ stm_act stm_mdl tst_mss_or_dst tst_mth df   logLik  AICc delta
## 4028       +       +       +              +       + 17 -292.796 626.6  0.00
## 4026       +       +       +              +       + 16 -294.767 627.7  1.09
## 4090       +       +       +              +       + 17 -293.488 628.0  1.38
## 1980       +       +       +              +         16 -294.968 628.1  1.49
##      weight
## 4028  0.166
## 4026  0.096
## 4090  0.083
## 1980  0.079
## Models ranked by AICc(x)

model selection

take everything

rma.glmulti <- function(formula,data)
  {rma.mv(formula, d_var_calc, data=ma_data, method="ML")
}

res_sink <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video + test_method, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)
## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
## 
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 725.864818541665

## 
## After 100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 715.577293551161

## 
## After 150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Crit= 685.621375640315
## Mean crit= 702.934590573398

## 
## After 200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Crit= 681.908005574812
## Mean crit= 692.58121918037

## 
## After 250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Crit= 679.326562070076
## Mean crit= 685.66494209925

## 
## After 300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Crit= 675.615212139058
## Mean crit= 683.087299477267

## 
## After 350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Crit= 675.615212139058
## Mean crit= 681.041840284071

## 
## After 400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Crit= 658.04629132771
## Mean crit= 674.609490842962

## 
## After 450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Crit= 658.04629132771
## Mean crit= 668.472326568765

## 
## After 500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 654.840389646851
## Mean crit= 661.80051897223

## 
## After 550 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181
## 
## After 600 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181

## 
## After 650 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181
## 
## After 700 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181
## 
## After 750 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181
## 
## After 800 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 656.348270487966
## 
## After 850 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 656.348270487966

## 
## After 900 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 656.348270487966
## 
## After 950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed+practice_phase
## Crit= 643.215901075392
## Mean crit= 652.239304622212
## 
## After 1000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed+practice_phase
## Crit= 643.215901075392
## Mean crit= 652.239304622212

## 
## After 1050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 649.217817133762

## 
## After 1100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
## 
## After 1150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953

## 
## After 1200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
## 
## After 1250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
## 
## After 1300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
## 
## After 1350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
## 
## After 1400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
## 
## After 1450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.80098079723
## 
## After 1500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.80098079723

## 
## After 1550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.774535022456

## 
## After 1600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 1650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648

## 
## After 1700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 1750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 1800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 1850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 1900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 1950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
## 
## After 2000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 644.161601224252
## 
## After 2050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 644.161601224252

## 
## After 2100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 643.526880484051

## 
## After 2150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535

## 
## After 2250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
## 
## After 2650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 2700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926

## 
## After 2750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 2800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 2850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 2900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 2950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 3000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
## 
## After 3050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.137366768907
## 
## After 3100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.137366768907

## 
## After 3150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.137366768907
## 
## After 3200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163

## 
## After 3300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 3950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 4000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 4050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 4100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 4150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 4200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
## 
## After 4250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546

## 
## After 4350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
## 
## After 4750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 637.74342984342

## 
## After 4800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 4850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134

## 
## After 4900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 4950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
## 
## After 5300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783

## 
## After 5400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
## 
## After 5850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 5900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095

## 
## After 5950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
## 
## After 6350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.412208996814

## 
## After 6400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827

## 
## After 6500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
## 
## After 6900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 6950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752

## 
## After 7000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
## 
## After 7400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.8141873625

## 
## After 7450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969

## 
## After 7550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
## 
## After 7950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062

## 
## After 8050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
## 
## After 8500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256

## 
## After 8600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 8950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 9950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 10950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
## 
## After 11650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 11700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738

## 
## After 11750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 11800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 11850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 11900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 11950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 12950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 13000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 13050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 13100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 13150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 13200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
## 
## After 13250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337

## 
## After 13350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
## 
## After 13800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 13850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383

## 
## After 13900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 13950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
## 
## After 14300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049

## 
## After 14400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 14950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
## 
## After 15350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 627.714907756343
## Mean crit= 630.098068933114

## 
## After 15400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788

## 
## After 15500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
## 
## After 15900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 15950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907

## 
## After 16000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
## 
## After 16400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.171128087261

## 
## After 16450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912

## 
## After 16550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
## 
## After 16950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.594452184632

## Completed.
print(res_sink)
## glmulti.analysis
## Method: h / Fitting: rma.glmulti / IC used: aicc
## Level: 1 / Marginality: FALSE
## From 32 models:
## Best IC: 626.162713518951
## Best model:
## [1] "d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + "       
## [2] "    test_type + stimuli_actor + stimuli_modality + presentation_type + "       
## [3] "    test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + "
## [4] "    test_method"                                                               
## Evidence weight: 0.0868908971237817
## Worst IC: 629.815123421915
## 12 models within 2 IC units.
## 28 models to reach 95% of evidence weight.
top <- weightable(res_sink)
top <- top[top$aicc <= min(top$aicc) + 2,]
top
##                                                                                                                                                                                                                                                                              model
## 1                                                  d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 2                             d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 3                                   d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 4              d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 5  d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 6                       d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 7                                                              d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 8                                         d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 9                        d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video + test_method
## 10                                            d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video + test_method
## 11                                                d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## 12                           d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
##        aicc    weights
## 1  626.1627 0.08689090
## 2  626.1627 0.08689090
## 3  626.6273 0.06887925
## 4  626.6273 0.06887925
## 5  626.8462 0.06173869
## 6  626.8462 0.06173869
## 7  627.7149 0.03998707
## 8  627.7149 0.03998707
## 9  628.0097 0.03450715
## 10 628.0097 0.03450715
## 11 628.1178 0.03269093
## 12 628.1178 0.03269093
summary(res_sink@objects[[1]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -292.5641   609.3440   619.1282   664.2456   626.1627   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 88) = 609.3440, p-val < .0001
## 
## Test of Moderators (coefficients 2:17):
## QM(df = 16) = 174.5274, p-val < .0001
## 
## Model Results:
## 
##                                             estimate      se     zval    pval 
## intrcpt                                      -0.3715  0.2437  -1.5247  0.1273 
## agent_argument_type_cleannoun_phrase         -0.0294  0.1515  -0.1940  0.8462 
## agent_argument_type_cleanpronoun             -1.1277  0.1863  -6.0544  <.0001 
## agent_argument_type_cleanvarying_agent        0.2101  0.1700   1.2360  0.2165 
## patient_argument_type_cleannoun              -0.1101  0.1027  -1.0720  0.2837 
## patient_argument_type_cleannoun_phrase        0.9547  0.1547   6.1722  <.0001 
## patient_argument_type_cleanpronoun            1.0107  0.1461   6.9186  <.0001 
## patient_argument_type_cleanvarying_patient   -0.6173  0.1658  -3.7225  0.0002 
## test_typeagent                               -0.4712  0.2245  -2.0988  0.0358 
## stimuli_actorperson                          -0.7062  0.1255  -5.6266  <.0001 
## stimuli_modalityvideo                         1.0359  0.1535   6.7497  <.0001 
## presentation_typeimmediate_after              0.8181  0.1958   4.1784  <.0001 
## presentation_typesimultaneous                 0.4582  0.1925   2.3797  0.0173 
## test_mass_or_distributedmass                  0.5228  0.1174   4.4544  <.0001 
## n_repetitions_sentence                        0.0273  0.0099   2.7607  0.0058 
## n_repetitions_video                          -0.1337  0.0358  -3.7316  0.0002 
## test_methodpoint                              0.3894  0.1397   2.7870  0.0053 
##                                               ci.lb    ci.ub 
## intrcpt                                     -0.8491   0.1061      
## agent_argument_type_cleannoun_phrase        -0.3262   0.2675      
## agent_argument_type_cleanpronoun            -1.4928  -0.7626  *** 
## agent_argument_type_cleanvarying_agent      -0.1231   0.5434      
## patient_argument_type_cleannoun             -0.3114   0.0912      
## patient_argument_type_cleannoun_phrase       0.6515   1.2579  *** 
## patient_argument_type_cleanpronoun           0.7244   1.2970  *** 
## patient_argument_type_cleanvarying_patient  -0.9423  -0.2923  *** 
## test_typeagent                              -0.9112  -0.0312    * 
## stimuli_actorperson                         -0.9522  -0.4602  *** 
## stimuli_modalityvideo                        0.7351   1.3367  *** 
## presentation_typeimmediate_after             0.4344   1.2018  *** 
## presentation_typesimultaneous                0.0808   0.8355    * 
## test_mass_or_distributedmass                 0.2928   0.7529  *** 
## n_repetitions_sentence                       0.0079   0.0466   ** 
## n_repetitions_video                         -0.2039  -0.0635  *** 
## test_methodpoint                             0.1156   0.6633   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_sink, type="s")
summary(res_sink@objects[[2]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -292.5641   609.3440   619.1282   664.2456   626.1627   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 88) = 609.3440, p-val < .0001
## 
## Test of Moderators (coefficients 2:17):
## QM(df = 16) = 174.5274, p-val < .0001
## 
## Model Results:
## 
##                                         estimate      se     zval    pval 
## intrcpt                                  -0.3715  0.2437  -1.5247  0.1273 
## sentence_structuretransitive             -0.6173  0.1658  -3.7225  0.0002 
## agent_argument_type_cleannoun_phrase     -0.0294  0.1515  -0.1940  0.8462 
## agent_argument_type_cleanpronoun         -1.1277  0.1863  -6.0544  <.0001 
## agent_argument_type_cleanvarying_agent    0.2101  0.1700   1.2360  0.2165 
## patient_argument_type_cleannoun           0.5072  0.1594   3.1829  0.0015 
## patient_argument_type_cleannoun_phrase    1.5720  0.2259   6.9581  <.0001 
## patient_argument_type_cleanpronoun        1.6280  0.2195   7.4154  <.0001 
## test_typeagent                           -0.4712  0.2245  -2.0988  0.0358 
## stimuli_actorperson                      -0.7062  0.1255  -5.6266  <.0001 
## stimuli_modalityvideo                     1.0359  0.1535   6.7497  <.0001 
## presentation_typeimmediate_after          0.8181  0.1958   4.1784  <.0001 
## presentation_typesimultaneous             0.4582  0.1925   2.3797  0.0173 
## test_mass_or_distributedmass              0.5228  0.1174   4.4544  <.0001 
## n_repetitions_sentence                    0.0273  0.0099   2.7607  0.0058 
## n_repetitions_video                      -0.1337  0.0358  -3.7316  0.0002 
## test_methodpoint                          0.3894  0.1397   2.7870  0.0053 
##                                           ci.lb    ci.ub 
## intrcpt                                 -0.8491   0.1061      
## sentence_structuretransitive            -0.9423  -0.2923  *** 
## agent_argument_type_cleannoun_phrase    -0.3262   0.2675      
## agent_argument_type_cleanpronoun        -1.4928  -0.7626  *** 
## agent_argument_type_cleanvarying_agent  -0.1231   0.5434      
## patient_argument_type_cleannoun          0.1949   0.8195   ** 
## patient_argument_type_cleannoun_phrase   1.1292   2.0148  *** 
## patient_argument_type_cleanpronoun       1.1977   2.0583  *** 
## test_typeagent                          -0.9112  -0.0312    * 
## stimuli_actorperson                     -0.9522  -0.4602  *** 
## stimuli_modalityvideo                    0.7351   1.3367  *** 
## presentation_typeimmediate_after         0.4344   1.2018  *** 
## presentation_typesimultaneous            0.0808   0.8355    * 
## test_mass_or_distributedmass             0.2928   0.7529  *** 
## n_repetitions_sentence                   0.0079   0.0466   ** 
## n_repetitions_video                     -0.2039  -0.0635  *** 
## test_methodpoint                         0.1156   0.6633   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_sink, type="s")

eval(metafor:::.glmulti)
coef(res_sink)
##                                                 Estimate Uncond. variance
## mean_age                                   -5.717145e-06     7.855875e-10
## practice_phaseyes                           3.076182e-02     3.846448e-03
## test_typeagent                             -1.973216e-01     6.627146e-02
## sentence_structuretransitive               -3.244215e-01     1.192952e-01
## patient_argument_type_cleanvarying_patient -3.244215e-01     1.192952e-01
## character_identificationyes                 9.760541e-02     1.392176e-02
## test_methodpoint                            2.845269e-01     3.135633e-02
## n_repetitions_sentence                      2.438700e-02     1.133115e-04
## intrcpt                                    -3.214126e-01     6.976540e-02
## agent_argument_type_cleannoun_phrase       -3.280362e-02     2.323232e-02
## agent_argument_type_cleanpronoun           -1.128194e+00     3.643199e-02
## agent_argument_type_cleanvarying_agent      2.277545e-01     3.180320e-02
## patient_argument_type_cleannoun             2.018958e-01     1.236271e-01
## patient_argument_type_cleannoun_phrase      1.306063e+00     1.428847e-01
## patient_argument_type_cleanpronoun          1.346457e+00     1.415696e-01
## stimuli_actorperson                        -6.824526e-01     1.817586e-02
## stimuli_modalityvideo                       1.013606e+00     2.449866e-02
## presentation_typeimmediate_after            7.555101e-01     4.135693e-02
## presentation_typesimultaneous               4.619675e-01     4.063332e-02
## test_mass_or_distributedmass                5.048201e-01     1.570356e-02
## n_repetitions_video                        -1.419722e-01     1.682711e-03
##                                            Nb models Importance
## mean_age                                           6  0.1059877
## practice_phaseyes                                 12  0.2541233
## test_typeagent                                    14  0.4753094
## sentence_structuretransitive                      16  0.5000000
## patient_argument_type_cleanvarying_patient        16  0.5000000
## character_identificationyes                       18  0.5298367
## test_methodpoint                                  24  0.8436815
## n_repetitions_sentence                            30  0.9705281
## intrcpt                                           32  1.0000000
## agent_argument_type_cleannoun_phrase              32  1.0000000
## agent_argument_type_cleanpronoun                  32  1.0000000
## agent_argument_type_cleanvarying_agent            32  1.0000000
## patient_argument_type_cleannoun                   32  1.0000000
## patient_argument_type_cleannoun_phrase            32  1.0000000
## patient_argument_type_cleanpronoun                32  1.0000000
## stimuli_actorperson                               32  1.0000000
## stimuli_modalityvideo                             32  1.0000000
## presentation_typeimmediate_after                  32  1.0000000
## presentation_typesimultaneous                     32  1.0000000
## test_mass_or_distributedmass                      32  1.0000000
## n_repetitions_video                               32  1.0000000
##                                            +/- (alpha=0.05)
## mean_age                                       5.493452e-05
## practice_phaseyes                              1.215565e-01
## test_typeagent                                 5.045583e-01
## sentence_structuretransitive                   6.769546e-01
## patient_argument_type_cleanvarying_patient     6.769546e-01
## character_identificationyes                    2.312572e-01
## test_methodpoint                               3.470649e-01
## n_repetitions_sentence                         2.086340e-02
## intrcpt                                        5.176881e-01
## agent_argument_type_cleannoun_phrase           2.987407e-01
## agent_argument_type_cleanpronoun               3.741016e-01
## agent_argument_type_cleanvarying_agent         3.495293e-01
## patient_argument_type_cleannoun                6.891359e-01
## patient_argument_type_cleannoun_phrase         7.408682e-01
## patient_argument_type_cleanpronoun             7.374509e-01
## stimuli_actorperson                            2.642382e-01
## stimuli_modalityvideo                          3.067745e-01
## presentation_typeimmediate_after               3.985862e-01
## presentation_typesimultaneous                  3.950838e-01
## test_mass_or_distributedmass                   2.456106e-01
## n_repetitions_video                            8.039940e-02
mmi <- as.data.frame(coef(res_sink))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)
##                                            Estimate Std. Error z value Pr(>|z|)
## intrcpt                                     -0.3214     0.2641 -1.2169   0.2237
## agent_argument_type_cleannoun_phrase        -0.0328     0.1524 -0.2152   0.8296
## agent_argument_type_cleanpronoun            -1.1282     0.1909 -5.9107   0.0000
## agent_argument_type_cleanvarying_agent       0.2278     0.1783  1.2771   0.2016
## patient_argument_type_cleannoun              0.2019     0.3516  0.5742   0.5658
## patient_argument_type_cleannoun_phrase       1.3061     0.3780  3.4552   0.0005
## patient_argument_type_cleanpronoun           1.3465     0.3763  3.5786   0.0003
## stimuli_actorperson                         -0.6825     0.1348 -5.0620   0.0000
## stimuli_modalityvideo                        1.0136     0.1565  6.4759   0.0000
## presentation_typeimmediate_after             0.7555     0.2034  3.7151   0.0002
## presentation_typesimultaneous                0.4620     0.2016  2.2918   0.0219
## test_mass_or_distributedmass                 0.5048     0.1253  4.0284   0.0001
## n_repetitions_video                         -0.1420     0.0410 -3.4610   0.0005
## n_repetitions_sentence                       0.0244     0.0106  2.2910   0.0220
## test_methodpoint                             0.2845     0.1771  1.6068   0.1081
## character_identificationyes                  0.0976     0.1180  0.8272   0.4081
## patient_argument_type_cleanvarying_patient  -0.3244     0.3454 -0.9393   0.3476
## sentence_structuretransitive                -0.3244     0.3454 -0.9393   0.3476
## test_typeagent                              -0.1973     0.2574 -0.7665   0.4434
## practice_phaseyes                            0.0308     0.0620  0.4960   0.6199
## mean_age                                     0.0000     0.0000 -0.2040   0.8384
##                                              ci.lb   ci.ub Importance
## intrcpt                                    -0.8391  0.1963     1.0000
## agent_argument_type_cleannoun_phrase       -0.3315  0.2659     1.0000
## agent_argument_type_cleanpronoun           -1.5023 -0.7541     1.0000
## agent_argument_type_cleanvarying_agent     -0.1218  0.5773     1.0000
## patient_argument_type_cleannoun            -0.4872  0.8910     1.0000
## patient_argument_type_cleannoun_phrase      0.5652  2.0469     1.0000
## patient_argument_type_cleanpronoun          0.6090  2.0839     1.0000
## stimuli_actorperson                        -0.9467 -0.4182     1.0000
## stimuli_modalityvideo                       0.7068  1.3204     1.0000
## presentation_typeimmediate_after            0.3569  1.1541     1.0000
## presentation_typesimultaneous               0.0669  0.8571     1.0000
## test_mass_or_distributedmass                0.2592  0.7504     1.0000
## n_repetitions_video                        -0.2224 -0.0616     1.0000
## n_repetitions_sentence                      0.0035  0.0453     0.9705
## test_methodpoint                           -0.0625  0.6316     0.8437
## character_identificationyes                -0.1337  0.3289     0.5298
## patient_argument_type_cleanvarying_patient -1.0014  0.3525     0.5000
## sentence_structuretransitive               -1.0014  0.3525     0.5000
## test_typeagent                             -0.7019  0.3072     0.4753
## practice_phaseyes                          -0.0908  0.1523     0.2541
## mean_age                                   -0.0001  0.0000     0.1060

three interdependence moderators, take one ### take test type

rma.glmulti <- function(formula,data)
  {rma.mv(formula, d_var_calc, data=ma_data, method="ML")
}

res_test_type <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor  + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)
## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
## 
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 725.864818541665

## 
## After 100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Crit= 681.908005574812
## Mean crit= 705.533482683937

## 
## After 150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Crit= 681.908005574812
## Mean crit= 693.779782457757

## 
## After 200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Crit= 676.702282084101
## Mean crit= 684.228322412755

## 
## After 250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 675.534339426318

## 
## After 300 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 673.113846675074

## 
## After 350 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 672.687365995921

## 
## After 400 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 671.779309026182

## 
## After 450 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 671.108211728166

## 
## After 500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 667.553576499284

## 
## After 550 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617
## 
## After 600 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617

## 
## After 650 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617
## 
## After 700 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617
## 
## After 750 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.3524303454

## 
## After 800 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803
## 
## After 850 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803

## 
## After 900 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803
## 
## After 950 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803
## 
## After 1000 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803
## 
## After 1050 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253
## 
## After 1100 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253

## 
## After 1150 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253
## 
## After 1200 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253
## 
## After 1250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253
## 
## After 1300 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.269476446531

## 
## After 1350 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677
## 
## After 1400 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677

## 
## After 1450 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677
## 
## After 1500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677
## 
## After 1550 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.123555700273

## 
## After 1600 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487
## 
## After 1650 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487

## 
## After 1700 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487
## 
## After 1750 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487
## 
## After 1800 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487
## 
## After 1850 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779
## 
## After 1900 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779

## 
## After 1950 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779
## 
## After 2000 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779
## 
## After 2050 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779
## 
## After 2100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.307531708463

## 
## After 2150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567

## 
## After 2250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 2950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 3950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 4000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 4050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 4100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 4150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 4200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## 
## After 4250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
## Completed.
print(res_test_type)
## glmulti.analysis
## Method: h / Fitting: rma.glmulti / IC used: aicc
## Level: 1 / Marginality: FALSE
## From 32 models:
## Best IC: 660.894852560475
## Best model:
## [1] "d_calc ~ 1 + sentence_structure + agent_argument_type_clean + "                   
## [2] "    patient_argument_type_clean + presentation_type + test_mass_or_distributed + "
## [3] "    practice_phase + character_identification + n_repetitions_sentence"           
## [1] "d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + "
## [2] "    presentation_type + test_mass_or_distributed + practice_phase + "   
## [3] "    character_identification + n_repetitions_sentence"                  
## Evidence weight: 0.0598302838054941
## Worst IC: 663.015244221681
## 28 models within 2 IC units.
## 29 models to reach 95% of evidence weight.
top <- weightable(res_test_type)
top <- top[top$aicc <= min(top$aicc) + 2,]
top
##                                                                                                                                                                                                                            model
## 1                  d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 2                                       d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 3                                             d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 4                        d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 5                                       d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 6                                                            d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 7                                                                        d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 8                                                   d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 9                                   d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 10                                                       d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 11      d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 12                           d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 13                                                                           d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 14                                                                                                d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 15                                          d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 16                                                               d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 17           d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 18                                d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 19                      d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 20 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 21                      d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 22                                           d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 23                                                      d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 24                                 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 25                                                           d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## 26                                                                                d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## 27                          d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 28     d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
##        aicc    weights
## 1  660.8949 0.05983028
## 2  660.8949 0.05983028
## 3  661.5400 0.04333476
## 4  661.5400 0.04333476
## 5  661.6089 0.04186702
## 6  661.6089 0.04186702
## 7  661.7956 0.03813436
## 8  661.7956 0.03813436
## 9  662.0483 0.03360882
## 10 662.0483 0.03360882
## 11 662.0817 0.03305251
## 12 662.0817 0.03305251
## 13 662.3370 0.02909195
## 14 662.3370 0.02909195
## 15 662.3376 0.02908232
## 16 662.3376 0.02908232
## 17 662.3737 0.02856237
## 18 662.3737 0.02856237
## 19 662.5565 0.02606714
## 20 662.5565 0.02606714
## 21 662.5650 0.02595685
## 22 662.5650 0.02595685
## 23 662.6773 0.02454008
## 24 662.6773 0.02454008
## 25 662.8049 0.02302266
## 26 662.8049 0.02302266
## 27 662.8900 0.02206418
## 28 662.8900 0.02206418
summary(res_test_type@objects[[1]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -314.1141   652.4440   656.2282   693.3836   660.8949   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
## 
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
## 
## Model Results:
## 
##                                         estimate      se     zval    pval 
## intrcpt                                  -0.4006  0.1987  -2.0164  0.0438 
## sentence_structuretransitive             -0.4510  0.1667  -2.7055  0.0068 
## agent_argument_type_cleannoun_phrase      0.1634  0.1458   1.1203  0.2626 
## agent_argument_type_cleanpronoun         -0.9581  0.1605  -5.9689  <.0001 
## agent_argument_type_cleanvarying_agent    0.2469  0.1580   1.5625  0.1182 
## patient_argument_type_cleannoun           0.3665  0.1592   2.3028  0.0213 
## patient_argument_type_cleannoun_phrase    1.4053  0.2104   6.6800  <.0001 
## patient_argument_type_cleanpronoun        1.5518  0.2273   6.8285  <.0001 
## presentation_typeimmediate_after          0.6529  0.1696   3.8486  0.0001 
## presentation_typesimultaneous             0.4518  0.1678   2.6928  0.0071 
## test_mass_or_distributedmass              0.3585  0.1009   3.5538  0.0004 
## practice_phaseyes                         0.1489  0.0762   1.9545  0.0506 
## character_identificationyes               0.2226  0.0903   2.4638  0.0137 
## n_repetitions_sentence                    0.0190  0.0094   2.0272  0.0426 
##                                           ci.lb    ci.ub 
## intrcpt                                 -0.7900  -0.0112    * 
## sentence_structuretransitive            -0.7778  -0.1243   ** 
## agent_argument_type_cleannoun_phrase    -0.1224   0.4491      
## agent_argument_type_cleanpronoun        -1.2727  -0.6435  *** 
## agent_argument_type_cleanvarying_agent  -0.0628   0.5567      
## patient_argument_type_cleannoun          0.0546   0.6784    * 
## patient_argument_type_cleannoun_phrase   0.9929   1.8176  *** 
## patient_argument_type_cleanpronoun       1.1064   1.9972  *** 
## presentation_typeimmediate_after         0.3204   0.9854  *** 
## presentation_typesimultaneous            0.1230   0.7807   ** 
## test_mass_or_distributedmass             0.1608   0.5562  *** 
## practice_phaseyes                       -0.0004   0.2982    . 
## character_identificationyes              0.0455   0.3996    * 
## n_repetitions_sentence                   0.0006   0.0373    * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_test_type, type="s")
summary(res_test_type@objects[[2]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -314.1141   652.4440   656.2282   693.3836   660.8949   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
## 
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
## 
## Model Results:
## 
##                                             estimate      se     zval    pval 
## intrcpt                                      -0.4006  0.1987  -2.0164  0.0438 
## agent_argument_type_cleannoun_phrase          0.1634  0.1458   1.1203  0.2626 
## agent_argument_type_cleanpronoun             -0.9581  0.1605  -5.9689  <.0001 
## agent_argument_type_cleanvarying_agent        0.2469  0.1580   1.5625  0.1182 
## patient_argument_type_cleannoun              -0.0846  0.1016  -0.8323  0.4053 
## patient_argument_type_cleannoun_phrase        0.9542  0.1402   6.8057  <.0001 
## patient_argument_type_cleanpronoun            1.1007  0.1458   7.5518  <.0001 
## patient_argument_type_cleanvarying_patient   -0.4510  0.1667  -2.7055  0.0068 
## presentation_typeimmediate_after              0.6529  0.1696   3.8486  0.0001 
## presentation_typesimultaneous                 0.4518  0.1678   2.6928  0.0071 
## test_mass_or_distributedmass                  0.3585  0.1009   3.5538  0.0004 
## practice_phaseyes                             0.1489  0.0762   1.9545  0.0506 
## character_identificationyes                   0.2226  0.0903   2.4638  0.0137 
## n_repetitions_sentence                        0.0190  0.0094   2.0272  0.0426 
##                                               ci.lb    ci.ub 
## intrcpt                                     -0.7900  -0.0112    * 
## agent_argument_type_cleannoun_phrase        -0.1224   0.4491      
## agent_argument_type_cleanpronoun            -1.2727  -0.6435  *** 
## agent_argument_type_cleanvarying_agent      -0.0628   0.5567      
## patient_argument_type_cleannoun             -0.2837   0.1146      
## patient_argument_type_cleannoun_phrase       0.6794   1.2290  *** 
## patient_argument_type_cleanpronoun           0.8151   1.3864  *** 
## patient_argument_type_cleanvarying_patient  -0.7778  -0.1243   ** 
## presentation_typeimmediate_after             0.3204   0.9854  *** 
## presentation_typesimultaneous                0.1230   0.7807   ** 
## test_mass_or_distributedmass                 0.1608   0.5562  *** 
## practice_phaseyes                           -0.0004   0.2982    . 
## character_identificationyes                  0.0455   0.3996    * 
## n_repetitions_sentence                       0.0006   0.0373    * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_test_type, type="s")

eval(metafor:::.glmulti)
coef(res_test_type)
##                                                 Estimate Uncond. variance
## stimuli_actorperson                        -0.0121306928     6.330089e-04
## test_typeagent                             -0.0748860964     1.855515e-02
## practice_phaseyes                           0.0620099120     7.223407e-03
## patient_argument_type_cleanvarying_patient -0.2043327785     5.474697e-02
## sentence_structuretransitive               -0.2043327785     5.474697e-02
## mean_age                                    0.0001747588     4.378124e-08
## character_identificationyes                 0.1302965213     1.404469e-02
## n_repetitions_sentence                      0.0144090061     1.337974e-04
## intrcpt                                    -0.4076971546     8.206490e-02
## agent_argument_type_cleannoun_phrase        0.2002873402     2.148478e-02
## agent_argument_type_cleanpronoun           -0.9798212355     3.259569e-02
## agent_argument_type_cleanvarying_agent      0.2048524412     2.644506e-02
## patient_argument_type_cleannoun             0.1217250140     5.937123e-02
## patient_argument_type_cleannoun_phrase      1.1291984096     7.458725e-02
## patient_argument_type_cleanpronoun          1.3065595657     7.755690e-02
## presentation_typeimmediate_after            0.6395098876     3.864976e-02
## presentation_typesimultaneous               0.3569413462     3.371999e-02
## test_mass_or_distributedmass                0.4186360679     1.295125e-02
##                                            Nb models Importance
## stimuli_actorperson                                4 0.09358327
## test_typeagent                                     8 0.23690084
## practice_phaseyes                                 14 0.43072200
## patient_argument_type_cleanvarying_patient        16 0.50000000
## sentence_structuretransitive                      16 0.50000000
## mean_age                                          16 0.51928651
## character_identificationyes                       22 0.69128421
## n_repetitions_sentence                            22 0.75403675
## intrcpt                                           32 1.00000000
## agent_argument_type_cleannoun_phrase              32 1.00000000
## agent_argument_type_cleanpronoun                  32 1.00000000
## agent_argument_type_cleanvarying_agent            32 1.00000000
## patient_argument_type_cleannoun                   32 1.00000000
## patient_argument_type_cleannoun_phrase            32 1.00000000
## patient_argument_type_cleanpronoun                32 1.00000000
## presentation_typeimmediate_after                  32 1.00000000
## presentation_typesimultaneous                     32 1.00000000
## test_mass_or_distributedmass                      32 1.00000000
##                                            +/- (alpha=0.05)
## stimuli_actorperson                            0.0493120431
## test_typeagent                                 0.2669809582
## practice_phaseyes                              0.1665785725
## patient_argument_type_cleanvarying_patient     0.4585937428
## sentence_structuretransitive                   0.4585937428
## mean_age                                       0.0004101022
## character_identificationyes                    0.2322759075
## n_repetitions_sentence                         0.0226710690
## intrcpt                                        0.5614703338
## agent_argument_type_cleannoun_phrase           0.2872853853
## agent_argument_type_cleanpronoun               0.3538573248
## agent_argument_type_cleanvarying_agent         0.3187280829
## patient_argument_type_cleannoun                0.4775689864
## patient_argument_type_cleannoun_phrase         0.5352792343
## patient_argument_type_cleanpronoun             0.5458311269
## presentation_typeimmediate_after               0.3853199390
## presentation_typesimultaneous                  0.3599082704
## test_mass_or_distributedmass                   0.2230509126
mmi <- as.data.frame(coef(res_test_type))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)
##                                            Estimate Std. Error z value Pr(>|z|)
## intrcpt                                     -0.4077     0.2865 -1.4232   0.1547
## agent_argument_type_cleannoun_phrase         0.2003     0.1466  1.3664   0.1718
## agent_argument_type_cleanpronoun            -0.9798     0.1805 -5.4271   0.0000
## agent_argument_type_cleanvarying_agent       0.2049     0.1626  1.2597   0.2078
## patient_argument_type_cleannoun              0.1217     0.2437  0.4996   0.6174
## patient_argument_type_cleannoun_phrase       1.1292     0.2731  4.1346   0.0000
## patient_argument_type_cleanpronoun           1.3066     0.2785  4.6916   0.0000
## presentation_typeimmediate_after             0.6395     0.1966  3.2529   0.0011
## presentation_typesimultaneous                0.3569     0.1836  1.9438   0.0519
## test_mass_or_distributedmass                 0.4186     0.1138  3.6786   0.0002
## n_repetitions_sentence                       0.0144     0.0116  1.2457   0.2129
## character_identificationyes                  0.1303     0.1185  1.0995   0.2716
## mean_age                                     0.0002     0.0002  0.8352   0.4036
## sentence_structuretransitive                -0.2043     0.2340 -0.8733   0.3825
## patient_argument_type_cleanvarying_patient  -0.2043     0.2340 -0.8733   0.3825
## practice_phaseyes                            0.0620     0.0850  0.7296   0.4656
## test_typeagent                              -0.0749     0.1362 -0.5498   0.5825
## stimuli_actorperson                         -0.0121     0.0252 -0.4821   0.6297
##                                              ci.lb   ci.ub Importance
## intrcpt                                    -0.9692  0.1538     1.0000
## agent_argument_type_cleannoun_phrase       -0.0870  0.4876     1.0000
## agent_argument_type_cleanpronoun           -1.3337 -0.6260     1.0000
## agent_argument_type_cleanvarying_agent     -0.1139  0.5236     1.0000
## patient_argument_type_cleannoun            -0.3558  0.5993     1.0000
## patient_argument_type_cleannoun_phrase      0.5939  1.6645     1.0000
## patient_argument_type_cleanpronoun          0.7607  1.8524     1.0000
## presentation_typeimmediate_after            0.2542  1.0248     1.0000
## presentation_typesimultaneous              -0.0030  0.7168     1.0000
## test_mass_or_distributedmass                0.1956  0.6417     1.0000
## n_repetitions_sentence                     -0.0083  0.0371     0.7540
## character_identificationyes                -0.1020  0.3626     0.6913
## mean_age                                   -0.0002  0.0006     0.5193
## sentence_structuretransitive               -0.6629  0.2543     0.5000
## patient_argument_type_cleanvarying_patient -0.6629  0.2543     0.5000
## practice_phaseyes                          -0.1046  0.2286     0.4307
## test_typeagent                             -0.3419  0.1921     0.2369
## stimuli_actorperson                        -0.0614  0.0372     0.0936

take test method

res_test_method <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean  + stimuli_actor  + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video + test_method, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)
## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
## 
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Crit= 685.621375640315
## Mean crit= 719.578802019467

## 
## After 100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Crit= 676.702282084101
## Mean crit= 698.307675972734

## 
## After 150 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 685.05876444974

## 
## After 200 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 678.263457220778

## 
## After 250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 673.743174119515

## 
## After 300 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 670.987070822418

## 
## After 350 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 669.438547847758

## 
## After 400 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 665.399129492211
## 
## After 450 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 665.399129492211

## 
## After 500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 665.121127961905

## 
## After 550 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.989147048741
## 
## After 600 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.989147048741

## 
## After 650 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.696878763114

## 
## After 700 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.609770449294
## 
## After 750 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.609770449294

## 
## After 800 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.250100017641
## 
## After 850 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.250100017641

## 
## After 900 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.250100017641
## 
## After 950 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.95501513407
## 
## After 1000 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.95501513407

## 
## After 1050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.64582515669

## 
## After 1100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973

## 
## After 1200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 1950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
## 
## After 2000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642

## 
## After 2100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 2950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 3000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
## 
## After 3050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.510679707891
## 
## After 3100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.510679707891

## 
## After 3150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.510679707891
## 
## After 3200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882

## 
## After 3300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 3950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 4000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 4050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 4100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 4150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 4200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## 
## After 4250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
## Completed.
print(res)
## Global model call: rma.mv(yi = d_calc, V = d_var_calc, mods = ~mean_age + agent_argument_type_clean + 
##     patient_argument_type_clean + stimuli_modality + stimuli_actor + 
##     presentation_type + test_mass_or_distributed + practice_phase + 
##     character_identification + n_repetitions_sentence + n_repetitions_video + 
##     test_method, data = ma_data, method = "ML")
## ---
## Model selection table 
##      (Int) agn_arg_typ_cln chr_idn    men_age  n_rpt_snt  n_rpt_vid
## 4028     +               +       +             2.482e-02 -1.557e-01
## 4026     +               +                     2.037e-02 -1.422e-01
## 4090     +               +                     2.110e-02 -1.083e-01
## 1980     +               +       +             2.196e-02 -1.757e-01
## 4092     +               +       +             2.443e-02 -1.322e-01
## 4032     +               +       + -6.528e-05  2.476e-02 -1.582e-01
## 2044     +               +       +             2.166e-02 -1.446e-01
## 2042     +               +                     1.755e-02 -1.181e-01
## 4018     +               +                               -1.402e-01
## 4082     +               +                               -1.086e-01
## 4030     +               +          9.070e-05  2.086e-02 -1.399e-01
## 4020     +               +       +                       -1.493e-01
## 1984     +               +       +  1.257e-04  2.250e-02 -1.680e-01
## 2034     +               +                               -1.167e-01
## 1972     +               +       +                       -1.667e-01
## 4094     +               +          9.039e-06  2.114e-02 -1.083e-01
## 1978     +               +                     1.600e-02 -1.632e-01
## 1982     +               +          2.699e-04  1.881e-02 -1.500e-01
## 1970     +               +                               -1.587e-01
## 4096     +               +       + -9.424e-05  2.431e-02 -1.341e-01
## 2046     +               +          1.798e-04  1.916e-02 -1.168e-01
## 2036     +               +       +                       -1.340e-01
## 4074     +               +                     2.118e-02           
## 4084     +               +       +                       -1.230e-01
## 2048     +               +       +  8.919e-05  2.207e-02 -1.414e-01
## 4022     +               +          4.295e-05            -1.391e-01
## 1974     +               +          2.049e-04            -1.481e-01
## 2038     +               +          1.164e-04            -1.158e-01
## 4086     +               +         -3.697e-05            -1.084e-01
## 4024     +               +       + -7.645e-05            -1.522e-01
## 1976     +               +       +  8.849e-05            -1.611e-01
## 4066     +               +                                         
## 4076     +               +       +             2.211e-02           
## 2040     +               +       +  4.932e-05            -1.322e-01
## 4078     +               +         -2.502e-06  2.117e-02           
## 4088     +               +       + -1.089e-04            -1.253e-01
## 2026     +               +                     1.710e-02           
## 3896     +               +       + -3.662e-04            -1.411e-01
## 2018     +               +                                         
## 3960     +               +       + -3.991e-04            -1.100e-01
## 2030     +               +          1.956e-04  1.886e-02           
## 3904     +               +       + -3.599e-04  1.036e-02 -1.309e-01
## 4070     +               +         -4.858e-05                      
## 4068     +               +       +                                 
## 3892     +               +       +                       -1.278e-01
## 4080     +               +       + -3.214e-05  2.206e-02           
## 2028     +               +       +             1.840e-02           
## 3968     +               +       + -3.936e-04  1.070e-02 -9.859e-02
## 2022     +               +          1.330e-04                      
## 3900     +               +       +             1.081e-02 -1.175e-01
## 2020     +               +       +                                 
## 3958     +               +         -3.513e-04            -7.368e-02
## 3956     +               +       +                       -1.029e-01
## 2032     +               +       +  1.801e-04  1.937e-02           
## 1844     +               +       +                       -1.350e-01
## 3964     +               +       +             1.110e-02 -9.120e-02
## 4072     +               +       + -4.922e-05                      
## 1908     +               +       +                       -1.003e-01
## 3942     +               +         -3.401e-04                      
## 3954     +               +                               -7.132e-02
## 3952     +               +       + -3.594e-04  1.459e-02           
## 2024     +               +       +  1.396e-04                      
## 3950     +               +         -3.314e-04  1.083e-02           
## 4010     +               +                     1.944e-02           
## 3966     +               +         -3.440e-04  7.079e-03 -6.339e-02
## 956      +               +       +             3.340e-02 -1.998e-01
## 3944     +               +       + -3.616e-04                      
## 3938     +               +                                         
## 1020     +               +       +             3.258e-02 -1.579e-01
## 3890     +               +                               -1.088e-01
## 1912     +               +       + -1.734e-04            -1.027e-01
## 1848     +               +       + -1.186e-04            -1.405e-01
## 3946     +               +                     1.131e-02           
## 3894     +               +         -2.707e-04            -1.164e-01
## 3962     +               +                     7.772e-03 -6.007e-02
## 3948     +               +       +             1.470e-02           
## 1852     +               +       +             3.135e-03 -1.325e-01
## 4012     +               +       +             2.202e-02           
## 1018     +               +                     2.831e-02 -1.293e-01
## 4002     +               +                                         
## 1916     +               +       +             4.282e-03 -9.552e-02
## 4014     +               +          1.907e-04  2.049e-02           
## 1906     +               +                               -6.356e-02
## 3940     +               +       +                                 
## 1890     +               +                                         
## 960      +               +       + -1.418e-04  3.194e-02 -2.067e-01
## 1024     +               +       + -1.809e-04  3.064e-02 -1.629e-01
## 3898     +               +                     5.905e-03 -1.019e-01
## 1892     +               +       +                                 
## 3004     +               +       +             3.310e-02 -2.004e-01
## 3902     +               +         -2.631e-04  5.115e-03 -1.103e-01
## 1920     +               +       + -1.619e-04  2.850e-03 -9.935e-02
## 1856     +               +       + -1.098e-04  2.061e-03 -1.384e-01
## 3068     +               +       +             3.203e-02 -1.587e-01
## 4006     +               +          1.432e-04                      
## 4016     +               +       +  1.263e-04  2.223e-02           
## 4004     +               +       +                                 
## 1022     +               +         -7.428e-05  2.721e-02 -1.294e-01
## 1910     +               +         -1.098e-04            -6.314e-02
## 3066     +               +                     2.811e-02 -1.295e-01
## 1894     +               +         -1.141e-04                      
## 1900     +               +       +             7.749e-03           
## 1914     +               +                     4.205e-04 -6.287e-02
## 1898     +               +                     3.983e-03           
## 1896     +               +       + -1.518e-04                      
## 954      +               +                     2.721e-02 -1.868e-01
## 3008     +               +       + -1.871e-04  3.271e-02 -2.063e-01
## 3072     +               +       + -2.290e-04  3.145e-02 -1.624e-01
## 1966     +               +          4.372e-04  1.775e-02           
## 1958     +               +          3.737e-04                      
## 4008     +               +       +  1.097e-04                      
## 1842     +               +                               -1.134e-01
## 1904     +               +       + -1.263e-04  6.740e-03           
## 1918     +               +         -1.133e-04 -7.283e-04 -6.431e-02
## 3070     +               +         -9.630e-05  2.757e-02 -1.288e-01
## 1902     +               +         -9.941e-05  3.047e-03           
## 1724     +               +       +             2.436e-02 -9.189e-02
## 3884     +               +       +             1.715e-02           
## 958      +               +          3.672e-05  2.778e-02 -1.854e-01
## 1968     +               +       +  3.909e-04  1.908e-02           
## 3002     +               +                     2.773e-02 -1.859e-01
## 1728     +               +       +  2.269e-04  2.526e-02 -8.047e-02
## 3888     +               +       + -2.298e-04  1.733e-02           
## 1002     +               +                     2.842e-02           
## 1960     +               +       +  3.499e-04                      
## 1850     +               +                    -3.580e-03 -1.172e-01
## 1954     +               +                                         
## 3772     +               +       +             2.547e-02 -8.128e-02
## 1010     +               +                               -1.299e-01
## 1846     +               +          1.805e-05            -1.128e-01
## 1788     +               +       +             2.437e-02 -9.598e-02
## 1962     +               +                     1.278e-02           
## 3876     +               +       +                                 
## 1964     +               +       +             1.667e-02           
## 3882     +               +                     1.245e-02           
## 1956     +               +       +                                 
## 1014     +               +         -2.104e-04            -1.300e-01
## 3874     +               +                                         
## 3006     +               +          2.942e-05  2.790e-02 -1.852e-01
## 3880     +               +       + -2.232e-04                      
## 1016     +               +       + -2.989e-04            -1.541e-01
## 3058     +               +                               -1.324e-01
## 1716     +               +       +                       -7.945e-02
## 1004     +               +       +             2.980e-02           
## 1792     +               +       +  2.352e-04  2.533e-02 -8.967e-02
## 1012     +               +       +                       -1.444e-01
## 3776     +               +       +  2.032e-04  2.563e-02 -7.728e-02
## 1006     +               +         -7.191e-05  2.736e-02           
## 948      +               +       +                       -1.918e-01
## 3050     +               +                     2.879e-02           
## 1854     +               +         -2.290e-06 -3.609e-03 -1.173e-01
## 3886     +               +         -1.693e-04  1.229e-02           
## 952      +               +       + -2.588e-04            -2.051e-01
## 3878     +               +         -1.755e-04                      
## 3836     +               +       +             2.558e-02 -8.925e-02
## 1772     +               +       +             2.180e-02           
## 1712     +               +       +  3.662e-04  2.212e-02           
## 946      +               +                               -1.837e-01
## 3060     +               +       +                       -1.500e-01
## 1710     +               +          4.796e-04  1.943e-02           
## 3756     +               +       +             2.359e-02           
## 1726     +               +          4.400e-04  2.028e-02 -4.725e-02
## 1776     +               +       +  2.803e-04  2.315e-02           
## 1720     +               +       +  1.886e-04            -6.957e-02
## 2996     +               +       +                       -1.984e-01
## 3062     +               +         -1.688e-04            -1.311e-01
## 1774     +               +          4.095e-04  2.019e-02           
## 3820     +               +       +             2.387e-02           
## 1008     +               +       + -1.091e-04  2.858e-02           
## 3764     +               +       +                       -7.422e-02
## 3760     +               +       +  2.590e-04  2.391e-02           
## 1708     +               +       +             1.973e-02           
## 3064     +               +       + -2.678e-04            -1.546e-01
## 1780     +               +       +                       -8.260e-02
## 3052     +               +       +             3.007e-02           
## 3840     +               +       +  2.086e-04  2.577e-02 -8.733e-02
## 3054     +               +         -1.185e-04  2.811e-02           
## 1702     +               +          4.116e-04                      
## 1828     +               +       +                                 
## 2994     +               +                               -1.876e-01
## 950      +               +         -9.900e-05            -1.877e-01
## 1718     +               +          3.722e-04            -4.372e-02
## 3000     +               +       + -2.208e-04            -2.054e-01
## 3758     +               +          4.257e-04  2.026e-02           
## 1764     +               +       +                                 
## 1704     +               +       +  3.153e-04                      
## 3824     +               +       +  2.260e-04  2.412e-02           
## 1790     +               +          4.217e-04  2.039e-02 -3.746e-02
## 3774     +               +          4.357e-04  2.034e-02 -4.655e-02
## 1766     +               +          3.457e-04                      
## 1784     +               +       +  1.952e-04            -7.693e-02
## 3768     +               +       +  1.942e-04            -7.035e-02
## 1700     +               +       +                                 
## 1836     +               +       +             8.338e-03           
## 1768     +               +       +  2.374e-04                      
## 3748     +               +       +                                 
## 3822     +               +          3.935e-04  2.046e-02           
## 3056     +               +       + -1.701e-04  2.961e-02           
## 1770     +               +                     1.642e-02           
## 3828     +               +       +                       -7.908e-02
## 3750     +               +          3.780e-04                      
## 994      +               +                                         
## 1762     +               +                                         
## 1722     +               +                     1.568e-02 -5.840e-02
## 1832     +               +       +  2.156e-05                      
## 3812     +               +       +                                 
## 2998     +               +         -4.190e-05            -1.885e-01
## 1714     +               +                               -5.420e-02
## 3752     +               +       +  2.459e-04                      
## 1782     +               +          3.567e-04            -3.560e-02
## 3766     +               +          3.877e-04            -4.616e-02
## 1826     +               +                                         
## 3754     +               +                     1.762e-02           
## 998      +               +         -2.087e-04                      
## 3818     +               +                     1.811e-02           
## 3838     +               +          4.208e-04  2.041e-02 -3.734e-02
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## 3047     +                       + -7.345e-04                      
## 821      +                         -5.319e-04            -1.333e-01
## 2416     +               +       + -2.970e-04  5.437e-03           
## 3646     +               +          3.027e-05 -2.759e-03  2.965e-02
## 2999     +                       + -7.432e-04            -1.517e-01
## 3134     +               +          5.313e-05 -1.530e-03  4.244e-02
## 2424     +               +       + -3.143e-04             1.965e-02
## 3178     +               +                    -8.645e-03           
## 3118     +               +          5.557e-05 -7.538e-03           
## 1134     +               +          7.516e-05 -9.222e-03           
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## 2412     +               +       +             6.246e-03           
## 372      +               +       +                        1.574e-02
## 3710     +               +         -6.404e-06 -1.892e-03  6.010e-02
## 2472     +               +       +  9.473e-05                      
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## 2420     +               +       +                        1.357e-02
## 374      +               +         -2.874e-04             5.741e-02
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## 829      +                         -4.685e-04  6.868e-03 -1.249e-01
## 2860     +               +       +             1.719e-02           
## 804      +               +       +                                 
## 3174     +               +          7.522e-05                      
## 2856     +               +       + -3.644e-04                      
## 2869     +                         -6.023e-04            -1.333e-01
## 2432     +               +       + -3.092e-04  7.337e-03  2.858e-02
## 104      +               +       + -3.450e-04                      
## 2877     +                         -5.668e-04  9.736e-03 -1.216e-01
## 358      +               +         -2.461e-04                      
## 3994     +               +                     1.779e-02 -1.317e-01
## 2428     +               +       +             7.813e-03  2.318e-02
## 616      +               +       + -3.732e-04                      
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## 957      +                         -4.489e-04  1.502e-02 -1.264e-01
## 354      +               +                                         
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## 2422     +               +         -2.737e-04             5.706e-02
## 312      +               +       + -2.725e-04            -4.439e-02
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## 2418     +               +                                4.926e-02
## 2852     +               +       +                                 
## 3986     +               +                               -1.314e-01
## 112      +               +       + -3.168e-04  5.680e-03           
## 2152     +               +       + -2.844e-04                      
## 2402     +               +                                         
## 378      +               +                     7.039e-03  6.032e-02
## 624      +               +       + -3.419e-04  6.625e-03           
## 2148     +               +       +                                 
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## 120      +               +       + -3.460e-04             3.382e-03
## 296      +               +       + -2.554e-04                      
## 3005     +                         -5.260e-04  1.669e-02 -1.240e-01
## 308      +               +       +                       -4.141e-02
## 2664     +               +       + -3.230e-04                      
## 4050     +               +                               -1.055e-01
## 2406     +               +         -2.186e-04                      
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## 300      +               +       +             1.192e-02           
## 3996     +               +       +             1.844e-02 -1.332e-01
## 3998     +               +          7.846e-06  1.782e-02 -1.314e-01
## 40       +               +       + -2.819e-04                      
## 56       +               +       + -2.999e-04            -3.565e-02
## 3925     +                         -4.102e-04            -8.196e-02
## 304      +               +       + -2.129e-04  9.580e-03           
## 576      +               +       + -3.295e-04  5.217e-03 -5.520e-02
## 320      +               +       + -2.427e-04  6.205e-03 -3.846e-02
## 292      +               +       +                                 
## 100      +               +       +                                 
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## 362      +               +                     1.765e-03           
## 2997     +                         -5.452e-04            -1.310e-01
## 316      +               +       +             9.307e-03 -3.301e-02
## 2356     +               +       +                       -4.589e-02
## 2426     +               +                     4.135e-03  5.593e-02
## 2430     +               +         -2.699e-04  3.499e-03  6.259e-02
## 802      +               +                                         
## 2660     +               +       +                                 
## 3933     +                         -3.861e-04  9.195e-03 -6.599e-02
## 2360     +               +       + -2.536e-04            -4.509e-02
## 4062     +               +         -6.865e-05  1.784e-02 -1.043e-01
## 4060     +               +       +             1.783e-02 -1.022e-01
## 108      +               +       +             9.548e-03           
## 48       +               +       + -2.453e-04  8.570e-03           
## 552      +               +       + -3.034e-04                      
## 806      +               +         -2.011e-04                      
## 873      +                                     2.581e-02           
## 1001     +                                     2.173e-02           
## 3990     +               +         -2.461e-05            -1.322e-01
## 2160     +               +       + -2.781e-04  4.614e-03           
## 3988     +               +       +                       -1.313e-01
## 3993     +                                     1.511e-02 -9.582e-02
## 128      +               +       + -3.170e-04  6.223e-03  9.952e-03
## 2612     +               +       +                       -5.943e-02
## 827      +                       +             2.503e-02 -1.031e-01
## 2156     +               +       +             5.389e-03           
## 640      +               +       + -3.480e-04  5.610e-03 -2.307e-02
## 2410     +               +                    -1.541e-03           
## 2168     +               +       + -2.853e-04             1.892e-03
## 810      +               +                     8.799e-03           
## 44       +               +       +             1.119e-02           
## 4061     +                         -2.957e-04  1.432e-02 -7.374e-02
## 891      +                       +             2.659e-02 -6.704e-02
## 3927     +                       + -4.381e-04            -9.520e-02
## 4053     +                         -3.100e-04            -7.951e-02
## 2680     +               +       + -3.233e-04            -3.021e-02
## 2672     +               +       + -3.177e-04  5.953e-03           
## 36       +               +       +                                 
## 560      +               +       + -2.651e-04  9.536e-03           
## 2002     +               +                               -1.158e-01
## 3917     +                         -3.639e-04  1.371e-02           
## 3985     +                                               -1.017e-01
## 612      +               +       +                                 
## 2010     +               +                     1.414e-02 -1.164e-01
## 564      +               +       +                       -5.043e-02
## 2164     +               +       +                       -3.077e-03
## 2340     +               +       +                                 
## 2344     +               +       + -2.605e-04                      
## 4057     +                                     1.508e-02 -6.708e-02
## 889      +                                     2.320e-02 -4.571e-02
## 2939     +                       +             2.138e-02 -7.447e-02
## 64       +               +       + -2.722e-04  5.825e-03 -3.001e-02
## 4052     +               +       +                       -9.767e-02
## 1938     +               +                               -1.543e-01
## 4054     +               +         -1.010e-04            -1.052e-01
## 620      +               +       +             1.057e-02           
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## 3935     +                       + -4.176e-04  1.041e-02 -8.034e-02
## 2875     +                       +             2.023e-02 -1.128e-01
## 2921     +                                     2.171e-02           
## 2100     +               +       +                       -3.860e-02
## 875      +                       +             2.885e-02           
## 2348     +               +       +             1.096e-02           
## 2414     +               +         -2.255e-04 -2.637e-03           
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## 3863     +                       + -3.923e-04            -1.319e-01
## 1017     +                                     2.135e-02 -4.483e-02
## 986      +               +                     1.922e-02 -1.225e-01
## 52       +               +       +                       -3.148e-02
## 2104     +               +       + -2.515e-04            -3.777e-02
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## 2084     +               +       +                                 
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## 4049     +                                               -7.282e-02
## 2088     +               +       + -2.577e-04                      
## 4000     +               +       + -2.785e-05  1.844e-02 -1.345e-01
## 2364     +               +       +             6.835e-03 -3.833e-02
## 1583     +                       + -3.246e-04  1.176e-02           
## 2352     +               +       + -2.504e-04  1.047e-02           
## 2854     +               +         -3.007e-04                      
## 2937     +                                     1.822e-02 -5.140e-02
## 4041     +                                     1.647e-02           
## 2668     +               +       +             6.525e-03           
## 572      +               +       +             9.403e-03 -4.206e-02
## 814      +               +         -1.658e-04  6.698e-03           
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## 2624     +               +       + -3.093e-04  4.611e-03 -5.671e-02
## 2676     +               +       +                       -3.004e-02
## 3049     +                                     1.922e-02           
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## 2368     +               +       + -2.485e-04  6.387e-03 -3.804e-02
## 116      +               +       +                       -1.674e-03
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## 1950     +               +          2.192e-04  1.522e-02 -1.437e-01
## 60       +               +       +             9.303e-03 -2.308e-02
## 2923     +                       +             2.473e-02           
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## 2862     +               +         -2.965e-04  1.034e-02           
## 2850     +               +                                         
## 2092     +               +       +             9.137e-03           
## 548      +               +       +                                 
## 1942     +               +          1.733e-04            -1.434e-01
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## 2620     +               +       +             5.225e-03 -5.330e-02
## 124      +               +       +             1.008e-02  9.650e-03
## 3995     +                       +             1.572e-02 -9.727e-02
## 3909     +                         -3.956e-04                      
## 2600     +               +       + -2.909e-04                      
## 2096     +               +       + -2.491e-04  8.651e-03           
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## 3065     +                                     1.819e-02 -5.180e-02
## 4064     +               +       + -6.637e-05  1.779e-02 -1.039e-01
## 3034     +               +                     2.246e-02 -1.203e-01
## 4037     +                         -2.737e-04                      
## 955      +                       +             2.467e-02 -9.967e-02
## 3992     +               +       + -2.954e-05            -1.326e-01
## 4033     +                                                         
## 2176     +               +       + -2.812e-04  5.118e-03  7.779e-03
## 4034     +               +                                         
## 2858     +               +                     1.057e-02           
## 628      +               +       +                       -2.837e-02
## 2014     +               +          1.356e-04  1.528e-02 -1.151e-01
## 4044     +               +       +             1.664e-02           
## 1019     +                       +             2.357e-02 -5.817e-02
## 3929     +                                     1.113e-02 -5.971e-02
## 2172     +               +       +             5.617e-03  3.462e-03
## 815      +                       + -4.054e-04  2.094e-02           
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## 2863     +                       + -5.517e-04  2.483e-02           
## 3919     +                       + -3.736e-04  1.451e-02           
## 3921     +                                               -7.880e-02
## 2596     +               +       +                                 
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## 2688     +               +       + -3.191e-04  4.740e-03 -2.437e-02
## 2970     +               +                     2.242e-02 -1.598e-01
## 3987     +                       +                       -1.020e-01
## 2108     +               +       +             5.522e-03 -3.228e-02
## 1948     +               +       +             1.491e-02 -1.593e-01
## 4055     +                       + -3.156e-04            -8.103e-02
## 1940     +               +       +                       -1.553e-01
## 2004     +               +       +                       -1.129e-01
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## 2608     +               +       + -2.861e-04  1.000e-02           
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## 4059     +                       +             1.474e-02 -6.427e-02
## 4043     +                       +             1.491e-02           
## 2012     +               +       +             1.440e-02 -1.182e-01
## 953      +                                     2.092e-02 -9.503e-02
## 4036     +               +       +                                 
## 636      +               +       +             9.888e-03 -1.667e-02
## 2112     +               +       + -2.474e-04  5.074e-03 -3.198e-02
## 4056     +               +       + -7.131e-05            -9.944e-02
## 4051     +                       +                       -6.506e-02
## 2604     +               +       +             1.027e-02           
## 3857     +                                               -1.091e-01
## 4046     +               +         -7.605e-05  1.809e-02           
## 4035     +                       +                                 
## 1711     +                       + -3.076e-04  2.008e-02           
## 3869     +                         -2.845e-04  6.147e-03 -1.125e-01
## 1937     +                                               -1.341e-01
## 2001     +                                               -9.911e-02
## 1647     +                       + -3.485e-04  1.146e-02           
## 988      +               +       +             1.945e-02 -1.241e-01
## 990      +               +         -1.167e-05  1.902e-02 -1.225e-01
## 3003     +                       +             2.166e-02 -1.098e-01
## 3041     +                                                         
## 3067     +                       +             2.038e-02 -6.756e-02
## 978      +               +                               -1.244e-01
## 2684     +               +       +             5.362e-03 -2.343e-02
## 3631     +                       + -3.342e-04  1.194e-02           
## 1599     +                       + -3.243e-04  1.177e-02  1.503e-04
## 3051     +                       +             2.049e-02           
## 1639     +                       + -4.133e-04                      
## 924      +               +       +             2.030e-02 -1.686e-01
## 3057     +                                               -5.841e-02
## 993      +                                                         
## 4047     +                       + -2.401e-04  1.514e-02           
## 1591     +                       + -3.993e-04            -9.407e-03
## 3623     +                       + -3.529e-04                      
## 3926     +               +         -3.435e-04            -7.862e-02
## 3038     +               +         -1.662e-04  2.152e-02 -1.188e-01
## 4039     +                       + -2.341e-04                      
## 3859     +                       +                       -1.140e-01
## 3865     +                                     8.208e-03 -9.920e-02
## 926      +               +          7.116e-05  1.973e-02 -1.631e-01
## 1952     +               +       +  1.969e-04  1.561e-02 -1.458e-01
## 825      +                                     1.788e-02 -9.706e-02
## 3867     +                       +             1.084e-02 -1.026e-01
## 914      +               +                               -1.658e-01
## 1579     +                       +             1.586e-02           
## 1407     +                       + -3.288e-04  1.432e-02  7.891e-02
## 3931     +                       +             1.197e-02 -6.821e-02
## 3911     +                       + -3.921e-04                      
## 1944     +               +       +  1.753e-04            -1.432e-01
## 4038     +               +         -1.089e-04                      
## 1009     +                                               -4.848e-02
## 3001     +                                     1.829e-02 -1.027e-01
## 1945     +                                     8.550e-03 -1.347e-01
## 2009     +                                     8.836e-03 -9.918e-02
## 2972     +               +       +             2.358e-02 -1.621e-01
## 1405     +                         -2.871e-04  1.134e-02  1.013e-01
## 3923     +                       +                       -8.472e-02
## 2929     +                                               -8.186e-02
## 3036     +               +       +             2.246e-02 -1.203e-01
## 1397     +                         -3.680e-04             8.409e-02
## 2008     +               +       +  1.254e-04            -1.077e-01
## 1707     +                       +             2.205e-02           
## 2016     +               +       +  1.490e-04  1.498e-02 -1.122e-01
## 4048     +               +       + -9.520e-06  1.664e-02           
## 2974     +               +         -6.645e-05  2.205e-02 -1.615e-01
## 3627     +                       +             1.294e-02           
## 3915     +                       +             1.537e-02           
## 2867     +                       +                       -1.309e-01
## 1939     +                       +                       -1.349e-01
## 982      +               +         -1.079e-04            -1.241e-01
## 3934     +               +         -3.371e-04  7.681e-03 -6.747e-02
## 3922     +               +                               -7.527e-02
## 1941     +                          3.954e-05            -1.294e-01
## 3928     +               +       + -3.711e-04            -9.271e-02
## 4040     +               +       + -1.642e-05                      
## 3905     +                                                         
## 2873     +                                     1.393e-02 -1.041e-01
## 3864     +               +       + -3.324e-04            -1.297e-01
## 1663     +                       + -3.395e-04  1.216e-02  1.631e-02
## 2003     +                       +                       -9.710e-02
## 1399     +                       + -4.134e-04             6.471e-02
## 2005     +                         -1.725e-05            -1.004e-01
## 1775     +                       + -3.348e-04  1.994e-02           
## 3059     +                       +                       -6.826e-02
## 1727     +                       + -3.318e-04  2.010e-02 -8.312e-03
## 980      +               +       +                       -1.187e-01
## 3687     +                       + -3.726e-04                      
## 1703     +                       + -3.440e-04                      
## 1986     +               +                                         
## 1595     +                       +             1.662e-02  2.118e-02
## 3759     +                       + -3.129e-04  2.018e-02           
## 3695     +                       + -3.468e-04  1.141e-02           
## 3026     +               +                               -1.239e-01
## 3043     +                       +                                 
## 1994     +               +                     1.391e-02           
## 992      +               +       + -1.996e-05  1.920e-02 -1.247e-01
## 2931     +                       +                       -9.965e-02
## 1401     +                                     1.591e-02  1.043e-01
## 3619     +                       +                                 
## 1655     +                       + -4.126e-04             2.507e-03
## 3647     +                       + -3.331e-04  1.205e-02  1.281e-03
## 3639     +                       + -3.624e-04            -1.251e-02
## 928      +               +       +  1.751e-05  2.051e-02 -1.677e-01
## 3918     +               +         -3.203e-04  1.163e-02           
## 995      +                       +                                 
## 3910     +               +         -3.265e-04                      
## 2993     +                                               -1.096e-01
## 3755     +                       +             1.948e-02           
## 3858     +               +                               -1.100e-01
## 3862     +               +         -2.604e-04            -1.192e-01
## 2962     +               +                               -1.633e-01
## 1643     +                       +             1.586e-02           
## 2995     +                       +                       -1.160e-01
## 1947     +                       +             9.959e-03 -1.360e-01
## 945      +                                               -9.731e-02
## 916      +               +       +                       -1.667e-01
## 1873     +                                               -8.914e-02
## 3040     +               +       + -1.899e-04  2.201e-02 -1.236e-01
## 1403     +                       +             1.879e-02  8.687e-02
## 918      +               +         -2.443e-05            -1.670e-01
## 2976     +               +       + -1.495e-04  2.329e-02 -1.671e-01
## 1949     +                          6.968e-05  9.433e-03 -1.264e-01
## 3455     +                       + -3.399e-04  1.469e-02  8.048e-02
## 3930     +               +                     8.243e-03 -6.337e-02
## 3936     +               +       + -3.682e-04  8.869e-03 -8.213e-02
## 943      +                       + -3.672e-04  2.214e-02           
## 3977     +                                     1.813e-02           
## 3860     +               +       +                       -1.159e-01
## 1011     +                       +                       -5.329e-02
## 2865     +                                               -1.198e-01
## 3872     +               +       + -3.290e-04  8.633e-03 -1.199e-01
## 290      +               +                                         
## 1723     +                       +             2.166e-02  1.765e-02
## 2013     +                          1.285e-05  8.994e-03 -9.825e-02
## 2011     +                       +             9.002e-03 -1.003e-01
## 3030     +               +         -2.191e-04            -1.218e-01
## 3914     +               +                     1.194e-02           
## 1988     +               +       +                                 
## 3445     +                         -3.336e-04             8.170e-02
## 3453     +                         -3.001e-04  1.179e-02  1.031e-01
## 1771     +                       +             2.199e-02           
## 3906     +               +                                         
## 1571     +                       +                                 
## 970      +               +                     1.974e-02           
## 2991     +                       + -5.177e-04  2.523e-02           
## 3978     +               +                     1.764e-02           
## 3643     +                       +             1.374e-02  9.468e-03
## 947      +                       +                       -1.005e-01
## 3924     +               +       +                       -8.418e-02
## 3907     +                       +                                 
## 1998     +               +          1.547e-04  1.521e-02           
## 3691     +                       +             1.291e-02           
## 1943     +                       +  1.173e-05            -1.334e-01
## 1383     +                       + -4.303e-04                      
## 1996     +               +       +             1.243e-02           
## 3866     +               +                     6.968e-03 -1.015e-01
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## 2261     +                         -6.560e-05            -1.328e-03
## 2769     +                                               -1.016e-02
## 2075     +                       +             7.974e-03 -2.472e-02
## 2693     +                         -2.720e-05                      
## 95       +                       + -1.513e-04  3.221e-03 -2.153e-02
## 2572     +               +       +             5.990e-03           
## 544      +               +       + -1.595e-04  1.522e-03 -3.341e-02
## 2717     +                         -9.546e-06  1.520e-02 -2.315e-02
## 2076     +               +       +             3.616e-03 -1.356e-02
## 2051     +                       +                                 
## 2334     +               +         -1.421e-04  1.752e-03 -4.459e-03
## 2591     +                       + -2.814e-04  6.310e-03 -4.234e-02
## 2579     +                       +                       -4.857e-02
## 595      +                       +                       -3.700e-02
## 3153     +                                                5.579e-02
## 2639     +                       + -2.865e-04  8.321e-03           
## 2143     +                       + -2.773e-04  6.836e-03 -7.726e-03
## 2131     +                       +                       -2.335e-02
## 2575     +                       + -2.572e-04  1.085e-02           
## 7        +                       + -4.389e-05                      
## 515      +                       +                                 
## 2709     +                         -3.034e-05            -3.141e-02
## 2647     +                       + -3.058e-04            -3.790e-02
## 591      +                       + -1.276e-04  4.784e-03           
## 2636     +               +       +             3.667e-03           
## 604      +               +       +             3.892e-03 -4.702e-03
## 2576     +               +       + -2.018e-04  6.050e-03           
## 2644     +               +       +                       -9.944e-03
## 2080     +               +       + -1.969e-04  3.477e-03 -1.441e-02
## 2567     +                       + -2.830e-04                      
## 2140     +               +       +             3.582e-03  8.223e-03
## 603      +                       +             7.100e-03 -2.988e-02
## 2571     +                       +             1.201e-02           
## 2587     +                       +             8.049e-03 -3.787e-02
## 3089     +                                                3.161e-02
## 2588     +               +       +             3.277e-03 -2.714e-02
## 523      +                       +             6.860e-03           
## 2627     +                       +                                 
## 2640     +               +       + -2.169e-04  3.565e-03           
## 2139     +                       +             8.439e-03 -1.059e-02
## 15       +                       +  5.879e-06  7.200e-03           
## 3073     +                                                         
## 2635     +                       +             9.955e-03           
## 2648     +               +       + -2.191e-04            -1.138e-02
## 2781     +                         -3.635e-05  1.498e-02 -1.504e-03
## 608      +               +       + -1.702e-04  1.838e-03 -8.984e-03
## 607      +                       + -1.570e-04  2.894e-03 -3.970e-02
## 1029     +                          2.660e-04                      
## 3665     +                                                6.720e-02
## 2144     +               +       + -2.099e-04  3.432e-03  8.860e-03
## 3074     +               +                                         
## 3090     +               +                                3.247e-02
## 2592     +               +       + -2.145e-04  3.086e-03 -2.970e-02
## 2773     +                         -5.818e-05            -8.558e-03
## 2655     +                       + -2.881e-04  6.601e-03 -2.738e-02
## 2563     +                       +                                 
## 3157     +                          8.168e-05             5.371e-02
## 2643     +                       +                       -3.983e-02
## 3081     +                                    -6.895e-03           
## 1030     +               +          2.470e-04                      
## 519      +                       + -5.069e-05                      
## 1109     +                          2.360e-04             4.004e-02
## 3161     +                                    -1.515e-03  5.285e-02
## 3154     +               +                                5.314e-02
## 3093     +                          1.355e-04             3.093e-02
## 3077     +                          1.434e-04                      
## 1037     +                          2.145e-04 -6.623e-03           
## 1097     +                                    -1.068e-02           
## 2652     +               +       +             3.381e-03 -5.498e-03
## 3078     +               +          1.545e-04                      
## 3082     +               +                    -6.412e-03           
## 1093     +                          2.153e-04                      
## 3137     +                                                         
## 1045     +                          3.044e-04             1.476e-02
## 3097     +                                    -3.280e-03  2.622e-02
## 2651     +                       +             8.300e-03 -2.646e-02
## 3094     +               +          1.498e-04             3.206e-02
## 1026     +               +                                         
## 1046     +               +          2.645e-04             2.387e-02
## 3601     +                                                3.366e-02
## 1034     +               +                    -9.276e-03           
## 1038     +               +          2.127e-04 -7.098e-03           
## 527      +                       + -9.965e-07  6.832e-03           
## 3585     +                                                         
## 3666     +               +                                6.899e-02
## 3602     +               +                                3.760e-02
## 3145     +                                    -7.661e-03           
## 2656     +               +       + -2.179e-04  3.191e-03 -7.180e-03
## 1621     +                          2.041e-04             5.344e-02
## 1106     +               +                                4.984e-02
## 3669     +                          6.049e-05             6.478e-02
## 1541     +                          2.689e-04                      
## 1110     +               +          2.165e-04             4.677e-02
## 1101     +                          1.465e-04 -7.495e-03           
## 3085     +                          1.111e-04 -5.882e-03           
## 3673     +                                    -2.975e-04  6.651e-02
## 3098     +               +                    -2.396e-03  2.891e-02
## 3138     +               +                                         
## 3586     +               +                                         
## 1618     +               +                                7.017e-02
## 1113     +                                    -9.129e-03  2.448e-02
## 1117     +                          1.935e-04 -4.304e-03  3.421e-02
## 3158     +               +          1.205e-04             5.079e-02
## 3593     +                                    -6.825e-03           
## 3165     +                          7.816e-05 -7.668e-04  5.231e-02
## 1094     +               +          2.352e-04                      
## 1617     +                                                5.638e-02
## 1105     +                                                3.484e-02
## 1542     +               +          2.434e-04                      
## 1033     +                                    -1.208e-02           
## 3141     +                          1.313e-04                      
## 1042     +               +                                1.948e-02
## 1089     +                                                         
## 1053     +                          2.454e-04 -5.570e-03  8.703e-03
## 3086     +               +          1.394e-04 -5.769e-03           
## 3589     +                          1.469e-04                      
## 1098     +               +                    -1.012e-02           
## 3101     +                          1.258e-04 -1.910e-03  2.784e-02
## 3605     +                          1.332e-04             3.239e-02
## 3162     +               +                    -2.118e-03  4.985e-02
## 1549     +                          2.161e-04 -6.614e-03           
## 1622     +               +          1.827e-04             6.400e-02
## 1090     +               +                                         
## 1114     +               +                    -6.839e-03  3.992e-02
## 1609     +                                    -1.052e-02           
## 1054     +               +          2.360e-04 -4.970e-03  1.771e-02
## 1558     +               +          2.547e-04             2.914e-02
## 3606     +               +          1.429e-04             3.665e-02
## 1625     +                                    -7.226e-03  4.272e-02
## 3146     +               +                    -7.047e-03           
## 3649     +                                                         
## 1557     +                          2.994e-04             1.707e-02
## 1538     +               +                                         
## 1605     +                          2.185e-04                      
## 3609     +                                    -3.088e-03  2.810e-02
## 3590     +               +          1.542e-04                      
## 3142     +               +          1.545e-04                      
## 3594     +               +                    -6.440e-03           
## 1102     +               +          1.880e-04 -7.848e-03           
## 1050     +               +                    -8.199e-03  1.010e-02
## 1546     +               +                    -9.236e-03           
## 3102     +               +          1.459e-04 -1.617e-03  2.967e-02
## 3149     +                          8.904e-05 -6.737e-03           
## 3670     +               +          9.733e-05             6.589e-02
## 1550     +               +          2.086e-04 -7.120e-03           
## 1629     +                          1.751e-04 -3.261e-03  4.769e-02
## 1118     +               +          1.921e-04 -4.460e-03  4.064e-02
## 1626     +               +                    -4.949e-03  6.078e-02
## 3657     +                                    -7.599e-03           
## 3610     +               +                    -1.735e-03  3.475e-02
## 3674     +               +                    -7.638e-04  6.756e-02
## 3597     +                          1.147e-04 -5.761e-03           
## 1613     +                          1.483e-04 -7.484e-03           
## 3677     +                          6.134e-05  2.147e-04  6.524e-02
## 1049     +                                    -1.245e-02 -1.197e-02
## 1554     +               +                                2.659e-02
## 1545     +                                    -1.163e-02           
## 3650     +               +                                         
## 1601     +                                                         
## 3166     +               +          1.169e-04 -1.520e-03  4.850e-02
## 3653     +                          1.351e-04                      
## 1606     +               +          2.314e-04                      
## 1565     +                          2.439e-04 -5.424e-03  1.024e-02
## 1610     +               +                    -1.007e-02           
## 3150     +               +          1.336e-04 -6.211e-03           
## 3613     +                          1.245e-04 -1.775e-03  2.928e-02
## 1602     +               +                                         
## 3598     +               +          1.387e-04 -5.786e-03           
## 1630     +               +          1.679e-04 -3.128e-03  5.856e-02
## 1566     +               +          2.308e-04 -4.407e-03  2.293e-02
## 1562     +               +                    -7.444e-03  1.652e-02
## 1025     +                                                         
## 3658     +               +                    -7.092e-03           
## 3614     +               +          1.406e-04 -1.045e-03  3.496e-02
## 1614     +               +          1.836e-04 -7.876e-03           
## 3654     +               +          1.542e-04                      
## 3661     +                          9.248e-05 -6.617e-03           
## 3678     +               +          9.664e-05 -3.620e-04  6.524e-02
## 1561     +                                    -1.211e-02 -8.960e-03
## 1537     +                                                         
## 65       +                                                         
## 1041     +                                               -8.511e-03
## 3662     +               +          1.326e-04 -6.242e-03           
## 594      +               +                                6.909e-02
## 577      +                                                         
## 593      +                                                3.828e-02
## 2        +               +                                         
## 82       +               +                                4.508e-02
## 73       +                                    -3.510e-03           
## 81       +                                                1.535e-02
## 1553     +                                               -1.344e-03
## 2113     +                                                         
## 69       +                          2.255e-05                      
## 2049     +                                                         
## 66       +               +                                         
## 10       +               +                    -5.666e-03           
## 585      +                                    -3.430e-03           
## 1        +                                                         
## 514      +               +                                         
## 74       +               +                    -7.072e-03           
## 2625     +                                                         
## 513      +                                                         
## 2129     +                                                1.803e-02
## 598      +               +         -3.247e-05             7.023e-02
## 602      +               +                    -1.595e-03  6.605e-02
## 2641     +                                                3.861e-02
## 2642     +               +                                6.917e-02
## 581      +                          9.271e-06                      
## 2561     +                                                         
## 18       +               +                                9.858e-03
## 597      +                         -1.684e-05             3.914e-02
## 601      +                                    -3.734e-04  3.742e-02
## 5        +                          1.066e-04                      
## 90       +               +                    -3.828e-03  3.939e-02
## 89       +                                    -2.618e-03  1.122e-02
## 6        +               +          4.442e-05                      
## 2050     +               +                                         
## 2121     +                                    -2.641e-03           
## 77       +                         -2.258e-05 -4.180e-03           
## 85       +                          1.807e-05             1.506e-02
## 2117     +                         -4.152e-05                      
## 2130     +               +                                4.513e-02
## 86       +               +         -1.839e-06             4.511e-02
## 578      +               +                                         
## 17       +                                               -1.738e-02
## 2065     +                                               -5.194e-03
## 2053     +                         -2.834e-05                      
## 2057     +                                    -5.500e-04           
## 9        +                                    -4.709e-03           
## 70       +               +          1.818e-05                      
## 2114     +               +                                         
## 517      +                          8.490e-05                      
## 522      +               +                    -5.682e-03           
## 521      +                                    -4.450e-03           
## 530      +               +                                1.862e-02
## 25       +                                    -5.832e-03 -2.063e-02
## 586      +               +                    -7.058e-03           
## 589      +                         -4.214e-05 -4.675e-03           
## 2645     +                         -1.047e-04             4.455e-02
## 21       +                          8.758e-05            -1.273e-02
## 26       +               +                    -5.275e-03  3.512e-03
## 14       +               +          1.468e-05 -5.468e-03           
## 2633     +                                    -3.363e-03           
## 2058     +               +                    -5.579e-03           
## 2133     +                         -7.813e-05             2.155e-02
## 529      +                                               -8.194e-03
## 2122     +               +                    -8.076e-03           
## 518      +               +          3.661e-05                      
## 2562     +               +                                         
## 2629     +                         -3.604e-05                      
## 78       +               +         -2.801e-05 -7.498e-03           
## 2137     +                                    -2.781e-04  1.747e-02
## 2649     +                                     1.687e-03  4.266e-02
## 2066     +               +                                1.130e-02
## 2569     +                                    -1.278e-03           
## 13       +                          8.974e-05 -1.807e-03           
## 2565     +                         -2.274e-05                      
## 22       +               +          4.686e-05             1.016e-02
## 2577     +                                                2.221e-03
## 606      +               +         -4.392e-05 -2.236e-03  6.637e-02
## 2650     +               +                    -2.188e-03  6.510e-02
## 2125     +                         -6.855e-05 -3.567e-03           
## 2646     +               +         -3.711e-05             7.035e-02
## 605      +                         -2.955e-05 -1.299e-03  3.678e-02
## 93       +                         -1.371e-05 -3.063e-03  1.074e-02
## 2054     +               +          3.121e-05                      
## 94       +               +         -2.525e-05 -4.218e-03  3.931e-02
## 2138     +               +                    -4.307e-03  3.856e-02
## 582      +               +          1.114e-05                      
## 2073     +                                    -2.021e-03 -8.655e-03
## 2626     +               +                                         
## 2134     +               +         -1.110e-05             4.538e-02
## 2069     +                         -2.172e-05            -4.664e-03
## 2061     +                         -3.548e-05 -9.866e-04           
## 537      +                                    -5.222e-03 -1.268e-02
## 525      +                          6.052e-05 -2.521e-03           
## 533      +                          8.053e-05            -4.761e-03
## 538      +               +                    -4.286e-03  1.260e-02
## 2118     +               +          2.263e-05                      
## 29       +                          3.871e-05 -4.426e-03 -1.779e-02
## 2578     +               +                                1.974e-02
## 2570     +               +                    -5.784e-03           
## 526      +               +          5.888e-06 -5.602e-03           
## 534      +               +          3.742e-05             1.867e-02
## 2634     +               +                    -8.269e-03           
## 2637     +                         -6.783e-05 -4.277e-03           
## 590      +               +         -3.595e-05 -7.604e-03           
## 2653     +                         -1.017e-04  7.253e-04  4.612e-02
## 30       +               +          1.831e-05 -4.975e-03  3.991e-03
## 2074     +               +                    -4.979e-03  4.245e-03
## 2141     +                         -8.321e-05 -1.126e-03  1.951e-02
## 2062     +               +          1.653e-05 -5.498e-03           
## 2566     +               +          2.833e-05                      
## 2126     +               +         -1.192e-06 -8.083e-03           
## 2573     +                         -3.481e-05 -1.705e-03           
## 2585     +                                    -1.319e-03 -2.677e-04
## 2581     +                         -2.643e-05             2.933e-03
## 2070     +               +          2.540e-05             1.106e-02
## 2654     +               +         -4.060e-05 -2.329e-03  6.612e-02
## 2142     +               +         -1.919e-05 -4.387e-03  3.888e-02
## 2077     +                         -3.369e-05 -2.409e-03 -8.499e-03
## 541      +                          3.923e-05 -3.795e-03 -9.782e-03
## 2630     +               +          1.990e-05                      
## 2586     +               +                    -3.939e-03  1.347e-02
## 542      +               +          1.499e-05 -4.044e-03  1.296e-02
## 2582     +               +          1.668e-05             1.953e-02
## 2574     +               +          1.292e-05 -5.719e-03           
## 2638     +               +         -4.741e-06 -8.297e-03           
## 2078     +               +          1.590e-05 -4.908e-03  4.191e-03
## 2589     +                         -3.479e-05 -1.717e-03 -8.192e-05
## 2590     +               +          9.827e-06 -3.898e-03  1.341e-02
##      ptn_arg_typ_cln prc_phs prs_typ stm_act stm_mdl tst_mss_or_dst tst_mth df
## 4028               +               +       +       +              +       + 17
## 4026               +               +       +       +              +       + 16
## 4090               +       +       +       +       +              +       + 17
## 1980               +               +       +       +              +         16
## 4092               +       +       +       +       +              +       + 18
## 4032               +               +       +       +              +       + 18
## 2044               +       +       +       +       +              +         17
## 2042               +       +       +       +       +              +         16
## 4018               +               +       +       +              +       + 15
## 4082               +       +       +       +       +              +       + 16
## 4030               +               +       +       +              +       + 17
## 4020               +               +       +       +              +       + 16
## 1984               +               +       +       +              +         17
## 2034               +       +       +       +       +              +         15
## 1972               +               +       +       +              +         15
## 4094               +       +       +       +       +              +       + 18
## 1978               +               +       +       +              +         15
## 1982               +               +       +       +              +         16
## 1970               +               +       +       +              +         14
## 4096               +       +       +       +       +              +       + 19
## 2046               +       +       +       +       +              +         17
## 2036               +       +       +       +       +              +         16
## 4074               +       +       +       +       +              +       + 16
## 4084               +       +       +       +       +              +       + 17
## 2048               +       +       +       +       +              +         18
## 4022               +               +       +       +              +       + 16
## 1974               +               +       +       +              +         15
## 2038               +       +       +       +       +              +         16
## 4086               +       +       +       +       +              +       + 17
## 4024               +               +       +       +              +       + 17
## 1976               +               +       +       +              +         16
## 4066               +       +       +       +       +              +       + 15
## 4076               +       +       +       +       +              +       + 17
## 2040               +       +       +       +       +              +         17
## 4078               +       +       +       +       +              +       + 17
## 4088               +       +       +       +       +              +       + 18
## 2026               +       +       +       +       +              +         15
## 3896               +                       +       +              +       + 15
## 2018               +       +       +       +       +              +         14
## 3960               +       +               +       +              +       + 16
## 2030               +       +       +       +       +              +         16
## 3904               +                       +       +              +       + 16
## 4070               +       +       +       +       +              +       + 16
## 4068               +       +       +       +       +              +       + 16
## 3892               +                       +       +              +       + 14
## 4080               +       +       +       +       +              +       + 18
## 2028               +       +       +       +       +              +         16
## 3968               +       +               +       +              +       + 17
## 2022               +       +       +       +       +              +         15
## 3900               +                       +       +              +       + 15
## 2020               +       +       +       +       +              +         15
## 3958               +       +               +       +              +       + 15
## 3956               +       +               +       +              +       + 15
## 2032               +       +       +       +       +              +         17
## 1844               +                       +       +              +         13
## 3964               +       +               +       +              +       + 16
## 4072               +       +       +       +       +              +       + 17
## 1908               +       +               +       +              +         14
## 3942               +       +               +       +              +       + 14
## 3954               +       +               +       +              +       + 14
## 3952               +       +               +       +              +       + 16
## 2024               +       +       +       +       +              +         16
## 3950               +       +               +       +              +       + 15
## 4010               +               +       +       +              +       + 15
## 3966               +       +               +       +              +       + 16
## 956                +               +       +       +                        15
## 3944               +       +               +       +              +       + 15
## 3938               +       +               +       +              +       + 13
## 1020               +       +       +       +       +                        16
## 3890               +                       +       +              +       + 13
## 1912               +       +               +       +              +         15
## 1848               +                       +       +              +         14
## 3946               +       +               +       +              +       + 14
## 3894               +                       +       +              +       + 14
## 3962               +       +               +       +              +       + 15
## 3948               +       +               +       +              +       + 15
## 1852               +                       +       +              +         14
## 4012               +               +       +       +              +       + 16
## 1018               +       +       +       +       +                        15
## 4002               +               +       +       +              +       + 14
## 1916               +       +               +       +              +         15
## 4014               +               +       +       +              +       + 16
## 1906               +       +               +       +              +         13
## 3940               +       +               +       +              +       + 14
## 1890               +       +               +       +              +         12
## 960                +               +       +       +                        16
## 1024               +       +       +       +       +                        17
## 3898               +                       +       +              +       + 14
## 1892               +       +               +       +              +         13
## 3004               +               +       +       +                      + 16
## 3902               +                       +       +              +       + 15
## 1920               +       +               +       +              +         16
## 1856               +                       +       +              +         15
## 3068               +       +       +       +       +                      + 17
## 4006               +               +       +       +              +       + 15
## 4016               +               +       +       +              +       + 17
## 4004               +               +       +       +              +       + 15
## 1022               +       +       +       +       +                        16
## 1910               +       +               +       +              +         14
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## 1016               +       +       +       +       +                        16
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## 1004               +       +       +       +       +                        15
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## 1012               +       +       +       +       +                        15
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## 1006               +       +       +       +       +                        15
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## 1854               +                       +       +              +         14
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## 952                +               +       +       +                        15
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## 1830               +                       +       +              +         12
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## 1000               +       +       +       +       +                        15
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## 896                +       +               +       +                        15
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## 2944               +       +               +       +                      + 16
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## 3248               +               +                              +       + 15
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## 1588               +                               +              +         12
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## 3496               +               +       +                      +       + 15
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## 236                +       +       +                                        13
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## 3124               +                                              +       + 12
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## 890                +       +               +       +                        13
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## 944                +               +       +       +                        15
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## 2176               +       +                                              + 14
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## 2858               +                       +       +                      + 12
## 628                +       +                       +                        12
## 2014                       +       +       +       +              +         13
## 4044                       +       +       +       +              +       + 13
## 1019               +       +       +       +       +                        13
## 3929                       +               +       +              +       +  8
## 2172               +       +                                              + 13
## 815                +                       +       +                        10
## 4063                       +       +       +       +              +       + 12
## 2863               +                       +       +                      + 11
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## 3921                       +               +       +              +       +  7
## 2596               +                               +                      + 11
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## 2688               +       +                       +                      + 15
## 2970                               +       +       +                      + 11
## 3987                               +       +       +              +       +  9
## 2108               +                                                      + 12
## 1948                               +       +       +              +         12
## 4055                       +       +       +       +              +       + 11
## 1940                               +       +       +              +         11
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## 3991                               +       +       +              +       + 10
## 2608               +                               +                      + 13
## 3913                       +               +       +              +       +  7
## 4059                       +       +       +       +              +       + 11
## 4043                       +       +       +       +              +       + 10
## 2012                       +       +       +       +              +         13
## 953                +               +       +       +                        11
## 4036                       +       +       +       +              +       + 12
## 636                +       +                       +                        13
## 2112               +                                                      + 13
## 4056                       +       +       +       +              +       + 14
## 4051                       +       +       +       +              +       + 10
## 2604               +                               +                      + 12
## 3857                                       +       +              +       +  6
## 4046                       +       +       +       +              +       + 13
## 4035                       +       +       +       +              +       +  9
## 1711               +               +               +              +         12
## 3869                                       +       +              +       +  8
## 1937                               +       +       +              +          7
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## 1647               +       +                       +              +         11
## 988                        +       +       +       +                        12
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## 3631               +                               +              +       + 11
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## 1639               +       +                       +              +         10
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## 993                +       +       +       +       +                        10
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## 1591               +                               +              +         10
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## 4039                       +       +       +       +              +       + 10
## 3859                                       +       +              +       +  7
## 3865                                       +       +              +       +  7
## 926                                +       +       +                        11
## 1952                               +       +       +              +         13
## 825                +                       +       +                         9
## 3867                                       +       +              +       +  8
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## 3931                       +               +       +              +       +  9
## 3911                       +               +       +              +       +  8
## 1944                               +       +       +              +         12
## 4038                       +       +       +       +              +       + 12
## 1009               +       +       +       +       +                        11
## 3001               +               +       +       +                      + 12
## 1945                               +       +       +              +          8
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## 2929               +       +               +       +                      + 10
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## 1707               +               +               +              +         11
## 2016                       +       +       +       +              +         14
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## 2974                               +       +       +                      + 12
## 3627               +                               +              +       + 10
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## 2867               +                       +       +                      + 10
## 1939                               +       +       +              +          8
## 982                        +       +       +       +                        11
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## 3922                       +               +       +              +       + 10
## 1941                               +       +       +              +          8
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## 3905                       +               +       +              +       +  6
## 2873               +                       +       +                      + 10
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## 2003                       +       +       +       +              +          9
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## 2005                       +       +       +       +              +          9
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## 3059               +       +       +       +       +                      + 13
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## 980                        +       +       +       +                        11
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## 1994                       +       +       +       +              +         11
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## 2931               +       +               +       +                      + 11
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## 3639               +                               +              +       + 11
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## 3862                                       +       +              +       + 10
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## 945                +               +       +       +                        10
## 916                                +       +       +                        10
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## 943                +               +       +       +                        12
## 3977                               +       +       +              +       +  8
## 3860                                       +       +              +       + 10
## 1011               +       +       +       +       +                        12
## 2865               +                       +       +                      +  9
## 3872                                       +       +              +       + 12
## 290                +                       +                                 9
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## 2013                       +       +       +       +              +         10
## 2011                       +       +       +       +              +         10
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## 3906                       +               +       +              +       +  9
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## 2991               +               +       +       +                      + 13
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## 3643               +                               +              +       + 11
## 947                +               +       +       +                        11
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## 3691               +       +                       +              +       + 11
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## 1327               +                       +                      +         10
## 3868                                       +       +              +       + 11
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## 3451               +       +               +                      +       + 12
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## 813                +                       +       +                         9
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## 306                +                       +                                10
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## 3431               +       +               +                      +       + 11
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## 1063               +                                              +          8
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## 1323               +                       +                      +          9
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## 3443               +       +               +                      +       + 11
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## 2915               +       +               +       +                      + 10
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## 314                +                       +                                11
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## 3983                               +       +       +              +       + 10
## 359                +       +               +                                 9
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## 1067               +                                              +          8
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## 883                +       +               +       +                        10
## 1823                                       +       +              +          8
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## 1567                                               +              +          7
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## 137                                +                                         4
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## 1615                       +                       +              +          7
## 3104                                                              +       + 10
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## 201                        +       +                                         5
## 3152                       +                                      +       + 10
## 671                                +               +                         8
## 3160                       +                                      +       + 10
## 97                 +       +                                                 6
## 279                                        +                                 5
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## 207                        +       +                                         7
## 2187                               +                                      +  6
## 2327                                       +                              +  6
## 2819                                       +       +                      +  5
## 2319                                       +                              +  6
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## 3679                       +                       +              +       +  9
## 715                        +       +               +                         7
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## 105                +       +                                                 7
## 651                                +               +                         6
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## 2453                               +       +                              +  7
## 2311                                       +                              +  5
## 219                        +       +                                         7
## 1119                       +                                      +          7
## 283                                        +                                 5
## 143                                +                                         6
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## 129                                +                                         3
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## 3616                                               +              +       + 11
## 3664                       +                       +              +       + 11
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## 561                +                               +                         7
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## 2324                                       +                              +  8
## 1624                       +                       +              +         10
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## 3672                       +                       +              +       + 11
## 1568                                               +              +         10
## 195                        +       +                                         5
## 193                        +       +                                         4
## 2715                               +               +                      +  8
## 4                                                                            5
## 2191                               +                                      +  7
## 2306                                       +                              +  6
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## 2335                                       +                              +  7
## 731                        +       +               +                         8
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## 2185                               +                                      +  5
## 2328                                       +                              +  9
## 274                                        +                                 6
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## 2439                               +       +                              +  7
## 273                                        +                                 3
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## 1631                       +                       +              +          8
## 2255                       +       +                                      +  8
## 649                                +               +                         5
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## 147                                +                                         5
## 259                                        +                                 3
## 663                                +               +                         7
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## 625                +       +                       +                         8
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## 3168                       +                                      +       + 11
## 205                        +       +                                         6
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## 288                                        +                                 9
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## 719                        +       +               +                         8
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## 659                                +               +                         6
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## 735                        +       +               +                         9
## 145                                +                                         4
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## 8                                                                            6
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## 665                                +               +                         6
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## 641                                +               +                         4
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## 643                                +               +                         5
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## 2179                               +                                      +  5
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## 2325                                       +                              +  5
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## 1632                       +                       +              +         11
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## 2116                       +                                              +  7
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## 657                                +               +                         5
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## 723                        +       +               +                         7
## 2329                                       +                              +  5
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## 645                                +               +                         5
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## 2071                                                                      +  5
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## 2060                                                                      +  7
## 2333                                       +                              +  6
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## 2205                               +                                      +  7
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## 661                                +               +                         6
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## 2628                       +                       +                      +  8
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## 596                        +                       +                         8
## 3                                                                            2
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## 2124                       +                                              +  8
## 2055                                                                      +  4
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## 2132                       +                                              +  8
## 2064                                                                      +  8
## 32                                                                           8
## 2067                                                                      +  4
## 540                                                +                         8
## 583                        +                       +                         5
## 2059                                                                      +  4
## 31                                                                           5
## 2197                               +                                      +  6
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## 2123                       +                                              +  5
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## 2572                                               +                      +  8
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## 2717                               +               +                      +  8
## 2076                                                                      +  8
## 2051                                                                      +  3
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## 2575                                               +                      +  6
## 7                                                                            3
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## 2140                       +                                              +  9
## 603                        +                       +                         6
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## 15                                                                           4
## 3073                                                              +       +  3
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## 607                        +                       +                         7
## 1029                                                              +          3
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## 2144                       +                                              + 10
## 3074                                                              +       +  6
## 3090                                                              +       +  7
## 2592                                               +                      + 10
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## 3081                                                              +       +  4
## 1030                                                              +          6
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## 1109                       +                                      +          5
## 3161                       +                                      +       +  6
## 3154                       +                                      +       +  8
## 3093                                                              +       +  5
## 3077                                                              +       +  4
## 1037                                                              +          4
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## 2652                       +                       +                      + 10
## 3078                                                              +       +  7
## 3082                                                              +       +  7
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## 1045                                                              +          4
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## 3094                                                              +       +  8
## 1026                                                              +          5
## 1046                                                              +          7
## 3601                                               +              +       +  5
## 1034                                                              +          6
## 1038                                                              +          7
## 527                                                +                         5
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## 1621                       +                       +              +          6
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## 1101                       +                                      +          5
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## 3098                                                              +       +  8
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## 1618                       +                       +              +          8
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## 1117                       +                                      +          6
## 3158                       +                                      +       +  9
## 3593                                               +              +       +  5
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## 1105                       +                                      +          4
## 1542                                               +              +          7
## 1033                                                              +          3
## 3141                       +                                      +       +  5
## 1042                                                              +          6
## 1089                       +                                      +          3
## 1053                                                              +          5
## 3086                                                              +       +  8
## 3589                                               +              +       +  5
## 1098                       +                                      +          7
## 3101                                                              +       +  6
## 3605                                               +              +       +  6
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## 1558                                               +              +          8
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## 1625                       +                       +              +          6
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## 1557                                               +              +          5
## 1538                                               +              +          6
## 1605                       +                       +              +          5
## 3609                                               +              +       +  6
## 3590                                               +              +       +  8
## 3142                       +                                      +       +  8
## 3594                                               +              +       +  8
## 1102                       +                                      +          8
## 1050                                                              +          7
## 1546                                               +              +          7
## 3102                                                              +       +  9
## 3149                       +                                      +       +  6
## 3670                       +                       +              +       + 10
## 1550                                               +              +          8
## 1629                       +                       +              +          7
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## 1626                       +                       +              +          9
## 3657                       +                       +              +       +  6
## 3610                                               +              +       +  9
## 3674                       +                       +              +       + 10
## 3597                                               +              +       +  6
## 1613                       +                       +              +          6
## 3677                       +                       +              +       +  8
## 1049                                                              +          4
## 1554                                               +              +          7
## 1545                                               +              +          4
## 3650                       +                       +              +       +  8
## 1601                       +                       +              +          4
## 3166                       +                                      +       + 10
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## 1606                       +                       +              +          8
## 1565                                               +              +          6
## 1610                       +                       +              +          8
## 3150                       +                                      +       +  9
## 3613                                               +              +       +  7
## 1602                       +                       +              +          7
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## 1630                       +                       +              +         10
## 1566                                               +              +          9
## 1562                                               +              +          8
## 1025                                                              +          2
## 3658                       +                       +              +       +  9
## 3614                                               +              +       + 10
## 1614                       +                       +              +          9
## 3654                       +                       +              +       +  9
## 3661                       +                       +              +       +  7
## 3678                       +                       +              +       + 11
## 1561                                               +              +          5
## 1537                                               +              +          3
## 65                         +                                                 2
## 1041                                                              +          3
## 3662                       +                       +              +       + 10
## 594                        +                       +                         7
## 577                        +                       +                         3
## 593                        +                       +                         4
## 2                                                                            4
## 82                         +                                                 6
## 73                         +                                                 3
## 81                         +                                                 3
## 1553                                               +              +          4
## 2113                       +                                              +  3
## 69                         +                                                 3
## 2049                                                                      +  2
## 66                         +                                                 5
## 10                                                                           5
## 585                        +                       +                         4
## 1                                                                            1
## 514                                                +                         5
## 74                         +                                                 6
## 2625                       +                       +                      +  4
## 513                                                +                         2
## 2129                       +                                              +  4
## 598                        +                       +                         8
## 602                        +                       +                         8
## 2641                       +                       +                      +  5
## 2642                       +                       +                      +  8
## 581                        +                       +                         4
## 2561                                               +                      +  3
## 18                                                                           5
## 597                        +                       +                         5
## 601                        +                       +                         5
## 5                                                                            2
## 90                         +                                                 7
## 89                         +                                                 4
## 6                                                                            5
## 2050                                                                      +  5
## 2121                       +                                              +  4
## 77                         +                                                 4
## 85                         +                                                 4
## 2117                       +                                              +  4
## 2130                       +                                              +  7
## 86                         +                                                 7
## 578                        +                       +                         6
## 17                                                                           2
## 2065                                                                      +  3
## 2053                                                                      +  3
## 2057                                                                      +  3
## 9                                                                            2
## 70                         +                                                 6
## 2114                       +                                              +  6
## 517                                                +                         3
## 522                                                +                         6
## 521                                                +                         3
## 530                                                +                         6
## 25                                                                           3
## 586                        +                       +                         7
## 589                        +                       +                         5
## 2645                       +                       +                      +  6
## 21                                                                           3
## 26                                                                           6
## 14                                                                           6
## 2633                       +                       +                      +  5
## 2058                                                                      +  6
## 2133                       +                                              +  5
## 529                                                +                         3
## 2122                       +                                              +  7
## 518                                                +                         6
## 2562                                               +                      +  6
## 2629                       +                       +                      +  5
## 78                         +                                                 7
## 2137                       +                                              +  5
## 2649                       +                       +                      +  6
## 2066                                                                      +  6
## 2569                                               +                      +  4
## 13                                                                           3
## 2565                                               +                      +  4
## 22                                                                           6
## 2577                                               +                      +  4
## 606                        +                       +                         9
## 2650                       +                       +                      +  9
## 2125                       +                                              +  5
## 2646                       +                       +                      +  9
## 605                        +                       +                         6
## 93                         +                                                 5
## 2054                                                                      +  6
## 94                         +                                                 8
## 2138                       +                                              +  8
## 582                        +                       +                         7
## 2073                                                                      +  4
## 2626                       +                       +                      +  7
## 2134                       +                                              +  8
## 2069                                                                      +  4
## 2061                                                                      +  4
## 537                                                +                         4
## 525                                                +                         4
## 533                                                +                         4
## 538                                                +                         7
## 2118                       +                                              +  7
## 29                                                                           4
## 2578                                               +                      +  7
## 2570                                               +                      +  7
## 526                                                +                         7
## 534                                                +                         7
## 2634                       +                       +                      +  8
## 2637                       +                       +                      +  6
## 590                        +                       +                         8
## 2653                       +                       +                      +  7
## 30                                                                           7
## 2074                                                                      +  7
## 2141                       +                                              +  6
## 2062                                                                      +  7
## 2566                                               +                      +  7
## 2126                       +                                              +  8
## 2573                                               +                      +  5
## 2585                                               +                      +  5
## 2581                                               +                      +  5
## 2070                                                                      +  7
## 2654                       +                       +                      + 10
## 2142                       +                                              +  9
## 2077                                                                      +  5
## 541                                                +                         5
## 2630                       +                       +                      +  8
## 2586                                               +                      +  8
## 542                                                +                         8
## 2582                                               +                      +  8
## 2574                                               +                      +  8
## 2638                       +                       +                      +  9
## 2078                                                                      +  8
## 2589                                               +                      +  6
## 2590                                               +                      +  9
##        logLik  AICc  delta weight
## 4028 -292.796 626.6   0.00  0.166
## 4026 -294.767 627.7   1.09  0.096
## 4090 -293.488 628.0   1.38  0.083
## 1980 -294.968 628.1   1.49  0.079
## 4092 -292.379 628.7   2.08  0.059
## 4032 -292.748 629.4   2.82  0.041
## 2044 -294.288 629.6   2.98  0.037
## 2042 -295.750 629.7   3.06  0.036
## 4018 -297.159 629.7   3.08  0.036
## 4082 -296.048 630.3   3.65  0.027
## 4030 -294.657 630.3   3.72  0.026
## 4020 -296.155 630.5   3.86  0.024
## 1984 -294.740 630.5   3.89  0.024
## 2034 -297.580 630.6   3.93  0.023
## 1972 -297.651 630.7   4.07  0.022
## 4094 -293.487 630.9   4.30  0.019
## 1978 -297.780 631.0   4.33  0.019
## 1982 -296.517 631.2   4.59  0.017
## 1970 -299.313 631.3   4.66  0.016
## 4096 -292.280 631.5   4.87  0.015
## 2046 -295.245 631.5   4.90  0.014
## 2036 -296.897 632.0   5.35  0.011
## 4074 -296.901 632.0   5.36  0.011
## 4084 -295.625 632.3   5.66  0.010
## 2048 -294.177 632.3   5.68  0.010
## 4022 -297.134 632.5   5.82  0.009
## 1974 -298.558 632.5   5.88  0.009
## 2038 -297.362 632.9   6.28  0.007
## 4086 -296.031 633.1   6.47  0.007
## 4024 -296.088 633.2   6.58  0.006
## 1976 -297.538 633.3   6.63  0.006
## 4066 -299.482 634.4   7.73  0.003
## 4076 -296.803 634.6   8.01  0.003
## 2040 -296.863 634.8   8.13  0.003
## 4078 -296.901 634.8   8.21  0.003
## 4088 -295.492 634.9   8.31  0.003
## 2026 -299.861 635.1   8.49  0.002
## 3896 -300.149 635.7   9.06  0.002
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## 3030 -337.918 703.2  76.60  0.000
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## 513  -378.882 761.9 135.25  0.000
## 2129 -376.743 761.9 135.26  0.000
## 598  -372.211 761.9 135.29  0.000
## 602  -372.216 761.9 135.30  0.000
## 2641 -375.678 762.0 135.34  0.000
## 2642 -372.238 762.0 135.35  0.000
## 581  -376.804 762.0 135.38  0.000
## 2561 -377.915 762.1 135.44  0.000
## 18   -375.744 762.1 135.47  0.000
## 597  -375.755 762.1 135.49  0.000
## 601  -375.767 762.1 135.51  0.000
## 5    -379.026 762.2 135.54  0.000
## 90   -373.512 762.2 135.55  0.000
## 89   -376.891 762.2 135.55  0.000
## 6    -375.797 762.2 135.57  0.000
## 2050 -375.806 762.2 135.59  0.000
## 2121 -376.961 762.3 135.70  0.000
## 77   -376.983 762.4 135.74  0.000
## 85   -376.993 762.4 135.76  0.000
## 2117 -377.019 762.4 135.81  0.000
## 2130 -373.670 762.5 135.87  0.000
## 86   -373.673 762.5 135.87  0.000
## 578  -374.825 762.5 135.88  0.000
## 17   -379.228 762.6 135.95  0.000
## 2065 -378.246 762.7 136.10  0.000
## 2053 -378.266 762.8 136.14  0.000
## 2057 -378.283 762.8 136.18  0.000
## 9    -379.376 762.9 136.24  0.000
## 70   -375.069 763.0 136.37  0.000
## 2114 -375.078 763.0 136.39  0.000
## 517  -378.399 763.0 136.41  0.000
## 522  -375.155 763.2 136.54  0.000
## 521  -378.479 763.2 136.57  0.000
## 530  -375.218 763.3 136.67  0.000
## 25   -378.557 763.4 136.72  0.000
## 586  -374.204 763.6 136.94  0.000
## 589  -376.508 763.6 136.99  0.000
## 2645 -375.418 763.7 137.06  0.000
## 21   -378.730 763.7 137.07  0.000
## 26   -375.436 763.7 137.10  0.000
## 14   -375.442 763.7 137.11  0.000
## 2633 -376.572 763.8 137.12  0.000
## 2058 -375.448 763.8 137.13  0.000
## 2133 -376.596 763.8 137.17  0.000
## 529  -378.785 763.8 137.18  0.000
## 2122 -374.375 763.9 137.28  0.000
## 518  -375.526 763.9 137.28  0.000
## 2562 -375.538 763.9 137.31  0.000
## 2629 -376.701 764.0 137.38  0.000
## 78   -374.433 764.0 137.39  0.000
## 2137 -376.742 764.1 137.46  0.000
## 2649 -375.649 764.2 137.53  0.000
## 2066 -375.659 764.2 137.55  0.000
## 2569 -377.890 764.2 137.55  0.000
## 13   -378.980 764.2 137.57  0.000
## 2565 -377.902 764.2 137.58  0.000
## 22   -375.675 764.2 137.58  0.000
## 2577 -377.909 764.2 137.59  0.000
## 606  -372.162 764.2 137.59  0.000
## 2650 -372.195 764.3 137.66  0.000
## 2125 -376.851 764.3 137.68  0.000
## 2646 -372.209 764.3 137.69  0.000
## 605  -375.736 764.3 137.70  0.000
## 93   -376.884 764.4 137.75  0.000
## 2054 -375.785 764.4 137.80  0.000
## 94   -373.495 764.5 137.86  0.000
## 2138 -373.499 764.5 137.87  0.000
## 582  -374.822 764.8 138.17  0.000
## 2073 -378.202 764.8 138.18  0.000
## 2626 -374.825 764.8 138.18  0.000
## 2134 -373.667 764.8 138.21  0.000
## 2069 -378.234 764.9 138.24  0.000
## 2061 -378.253 764.9 138.28  0.000
## 537  -378.260 764.9 138.29  0.000
## 525  -378.309 765.0 138.39  0.000
## 533  -378.367 765.1 138.51  0.000
## 538  -375.020 765.2 138.57  0.000
## 2118 -375.068 765.3 138.66  0.000
## 29   -378.498 765.4 138.77  0.000
## 2578 -375.153 765.5 138.83  0.000
## 2570 -375.154 765.5 138.84  0.000
## 526  -375.154 765.5 138.84  0.000
## 534  -375.174 765.5 138.88  0.000
## 2634 -374.088 765.7 139.05  0.000
## 2637 -376.464 765.8 139.16  0.000
## 590  -374.168 765.8 139.21  0.000
## 2653 -375.412 766.0 139.35  0.000
## 30   -375.426 766.0 139.38  0.000
## 2074 -375.431 766.0 139.39  0.000
## 2141 -376.583 766.0 139.40  0.000
## 2062 -375.442 766.0 139.41  0.000
## 2566 -375.521 766.2 139.57  0.000
## 2126 -374.375 766.2 139.62  0.000
## 2573 -377.861 766.3 139.70  0.000
## 2585 -377.890 766.4 139.76  0.000
## 2581 -377.891 766.4 139.76  0.000
## 2070 -375.646 766.4 139.82  0.000
## 2654 -372.161 766.7 140.04  0.000
## 2142 -373.492 766.9 140.25  0.000
## 2077 -378.175 767.0 140.33  0.000
## 541  -378.200 767.0 140.38  0.000
## 2630 -374.816 767.1 140.51  0.000
## 2586 -375.013 767.5 140.90  0.000
## 542  -375.014 767.5 140.90  0.000
## 2582 -375.147 767.8 141.17  0.000
## 2574 -375.150 767.8 141.17  0.000
## 2638 -374.087 768.1 141.44  0.000
## 2078 -375.426 768.4 141.72  0.000
## 2589 -377.861 768.6 141.95  0.000
## 2590 -375.011 769.9 143.29  0.000
## Models ranked by AICc(x)
top <- weightable(res_test_method)
top <- top[top$aicc <= min(top$aicc) + 2,]
top
##                                                                                                                                                                                                                            model
## 1                                       d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 2                  d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 3                        d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 4                                             d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 5                                                   d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 6                                                                        d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 7                                   d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 8                                                        d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 9                            d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 10      d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 11                                                                           d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 12                                                                                                d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 13                                          d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 14                                                               d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 15                      d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 16 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 17                                 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 18                                                      d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 19                                                           d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## 20                                                                                d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
##        aicc    weights
## 1  660.8949 0.06562237
## 2  660.8949 0.06562237
## 3  661.5400 0.04752994
## 4  661.5400 0.04752994
## 5  661.7956 0.04182609
## 6  661.7956 0.04182609
## 7  662.0483 0.03686245
## 8  662.0483 0.03686245
## 9  662.0817 0.03625228
## 10 662.0817 0.03625228
## 11 662.3370 0.03190830
## 12 662.3370 0.03190830
## 13 662.3376 0.03189774
## 14 662.3376 0.03189774
## 15 662.5565 0.02859067
## 16 662.5565 0.02859067
## 17 662.6773 0.02691577
## 18 662.6773 0.02691577
## 19 662.8049 0.02525145
## 20 662.8049 0.02525145
summary(res_test_method@objects[[1]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -314.1141   652.4440   656.2282   693.3836   660.8949   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
## 
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
## 
## Model Results:
## 
##                                             estimate      se     zval    pval 
## intrcpt                                      -0.4006  0.1987  -2.0164  0.0438 
## agent_argument_type_cleannoun_phrase          0.1634  0.1458   1.1203  0.2626 
## agent_argument_type_cleanpronoun             -0.9581  0.1605  -5.9689  <.0001 
## agent_argument_type_cleanvarying_agent        0.2469  0.1580   1.5625  0.1182 
## patient_argument_type_cleannoun              -0.0846  0.1016  -0.8323  0.4053 
## patient_argument_type_cleannoun_phrase        0.9542  0.1402   6.8057  <.0001 
## patient_argument_type_cleanpronoun            1.1007  0.1458   7.5518  <.0001 
## patient_argument_type_cleanvarying_patient   -0.4510  0.1667  -2.7055  0.0068 
## presentation_typeimmediate_after              0.6529  0.1696   3.8486  0.0001 
## presentation_typesimultaneous                 0.4518  0.1678   2.6928  0.0071 
## test_mass_or_distributedmass                  0.3585  0.1009   3.5538  0.0004 
## practice_phaseyes                             0.1489  0.0762   1.9545  0.0506 
## character_identificationyes                   0.2226  0.0903   2.4638  0.0137 
## n_repetitions_sentence                        0.0190  0.0094   2.0272  0.0426 
##                                               ci.lb    ci.ub 
## intrcpt                                     -0.7900  -0.0112    * 
## agent_argument_type_cleannoun_phrase        -0.1224   0.4491      
## agent_argument_type_cleanpronoun            -1.2727  -0.6435  *** 
## agent_argument_type_cleanvarying_agent      -0.0628   0.5567      
## patient_argument_type_cleannoun             -0.2837   0.1146      
## patient_argument_type_cleannoun_phrase       0.6794   1.2290  *** 
## patient_argument_type_cleanpronoun           0.8151   1.3864  *** 
## patient_argument_type_cleanvarying_patient  -0.7778  -0.1243   ** 
## presentation_typeimmediate_after             0.3204   0.9854  *** 
## presentation_typesimultaneous                0.1230   0.7807   ** 
## test_mass_or_distributedmass                 0.1608   0.5562  *** 
## practice_phaseyes                           -0.0004   0.2982    . 
## character_identificationyes                  0.0455   0.3996    * 
## n_repetitions_sentence                       0.0006   0.0373    * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_test_method, type="s")
summary(res_test_method@objects[[2]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -314.1141   652.4440   656.2282   693.3836   660.8949   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
## 
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
## 
## Model Results:
## 
##                                         estimate      se     zval    pval 
## intrcpt                                  -0.4006  0.1987  -2.0164  0.0438 
## sentence_structuretransitive             -0.4510  0.1667  -2.7055  0.0068 
## agent_argument_type_cleannoun_phrase      0.1634  0.1458   1.1203  0.2626 
## agent_argument_type_cleanpronoun         -0.9581  0.1605  -5.9689  <.0001 
## agent_argument_type_cleanvarying_agent    0.2469  0.1580   1.5625  0.1182 
## patient_argument_type_cleannoun           0.3665  0.1592   2.3028  0.0213 
## patient_argument_type_cleannoun_phrase    1.4053  0.2104   6.6800  <.0001 
## patient_argument_type_cleanpronoun        1.5518  0.2273   6.8285  <.0001 
## presentation_typeimmediate_after          0.6529  0.1696   3.8486  0.0001 
## presentation_typesimultaneous             0.4518  0.1678   2.6928  0.0071 
## test_mass_or_distributedmass              0.3585  0.1009   3.5538  0.0004 
## practice_phaseyes                         0.1489  0.0762   1.9545  0.0506 
## character_identificationyes               0.2226  0.0903   2.4638  0.0137 
## n_repetitions_sentence                    0.0190  0.0094   2.0272  0.0426 
##                                           ci.lb    ci.ub 
## intrcpt                                 -0.7900  -0.0112    * 
## sentence_structuretransitive            -0.7778  -0.1243   ** 
## agent_argument_type_cleannoun_phrase    -0.1224   0.4491      
## agent_argument_type_cleanpronoun        -1.2727  -0.6435  *** 
## agent_argument_type_cleanvarying_agent  -0.0628   0.5567      
## patient_argument_type_cleannoun          0.0546   0.6784    * 
## patient_argument_type_cleannoun_phrase   0.9929   1.8176  *** 
## patient_argument_type_cleanpronoun       1.1064   1.9972  *** 
## presentation_typeimmediate_after         0.3204   0.9854  *** 
## presentation_typesimultaneous            0.1230   0.7807   ** 
## test_mass_or_distributedmass             0.1608   0.5562  *** 
## practice_phaseyes                       -0.0004   0.2982    . 
## character_identificationyes              0.0455   0.3996    * 
## n_repetitions_sentence                   0.0006   0.0373    * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_test_method, type="s")

eval(metafor:::.glmulti)
coef(res_test_method)
##                                                 Estimate Uncond. variance
## n_repetitions_video                        -0.0012128767     7.412201e-06
## test_methodpoint                            0.0104179101     5.892855e-04
## stimuli_actorperson                        -0.0178686406     1.276884e-03
## mean_age                                    0.0001372364     3.601193e-08
## patient_argument_type_cleanvarying_patient -0.2034557802     5.441230e-02
## sentence_structuretransitive               -0.2034557802     5.441230e-02
## practice_phaseyes                           0.0737132825     8.448253e-03
## n_repetitions_sentence                      0.0127128160     1.324853e-04
## character_identificationyes                 0.1482561143     1.409528e-02
## intrcpt                                    -0.3468533752     7.810498e-02
## agent_argument_type_cleannoun_phrase        0.1951506287     2.170645e-02
## agent_argument_type_cleanpronoun           -0.9894954278     3.162697e-02
## agent_argument_type_cleanvarying_agent      0.1875619558     2.643901e-02
## patient_argument_type_cleannoun             0.1171260277     5.900592e-02
## patient_argument_type_cleannoun_phrase      1.1380758966     7.412955e-02
## patient_argument_type_cleanpronoun          1.3040830413     7.722776e-02
## presentation_typeimmediate_after            0.6017983845     3.621442e-02
## presentation_typesimultaneous               0.3409757341     3.432543e-02
## test_mass_or_distributedmass                0.4237189678     1.275075e-02
##                                            Nb models Importance
## n_repetitions_video                                2 0.03879071
## test_methodpoint                                   4 0.08632097
## stimuli_actorperson                                6 0.14055753
## mean_age                                          12 0.41506278
## patient_argument_type_cleanvarying_patient        16 0.50000000
## sentence_structuretransitive                      16 0.50000000
## practice_phaseyes                                 16 0.50133921
## n_repetitions_sentence                            20 0.69231080
## character_identificationyes                       24 0.75323808
## intrcpt                                           32 1.00000000
## agent_argument_type_cleannoun_phrase              32 1.00000000
## agent_argument_type_cleanpronoun                  32 1.00000000
## agent_argument_type_cleanvarying_agent            32 1.00000000
## patient_argument_type_cleannoun                   32 1.00000000
## patient_argument_type_cleannoun_phrase            32 1.00000000
## patient_argument_type_cleanpronoun                32 1.00000000
## presentation_typeimmediate_after                  32 1.00000000
## presentation_typesimultaneous                     32 1.00000000
## test_mass_or_distributedmass                      32 1.00000000
##                                            +/- (alpha=0.05)
## n_repetitions_video                            0.0053360721
## test_methodpoint                               0.0475785235
## stimuli_actorperson                            0.0700364072
## mean_age                                       0.0003719386
## patient_argument_type_cleanvarying_patient     0.4571899107
## sentence_structuretransitive                   0.4571899107
## practice_phaseyes                              0.1801488691
## n_repetitions_sentence                         0.0225596306
## character_identificationyes                    0.2326939045
## intrcpt                                        0.5477563949
## agent_argument_type_cleannoun_phrase           0.2887636105
## agent_argument_type_cleanpronoun               0.3485594822
## agent_argument_type_cleanvarying_agent         0.3186916488
## patient_argument_type_cleannoun                0.4760974652
## patient_argument_type_cleannoun_phrase         0.5336343553
## patient_argument_type_cleanpronoun             0.5446716902
## presentation_typeimmediate_after               0.3729828336
## presentation_typesimultaneous                  0.3631249418
## test_mass_or_distributedmass                   0.2213176272
mmi <- as.data.frame(coef(res_test_method))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)
##                                            Estimate Std. Error z value Pr(>|z|)
## intrcpt                                     -0.3469     0.2795 -1.2411   0.2146
## agent_argument_type_cleannoun_phrase         0.1952     0.1473  1.3246   0.1853
## agent_argument_type_cleanpronoun            -0.9895     0.1778 -5.5640   0.0000
## agent_argument_type_cleanvarying_agent       0.1876     0.1626  1.1535   0.2487
## patient_argument_type_cleannoun              0.1171     0.2429  0.4822   0.6297
## patient_argument_type_cleannoun_phrase       1.1381     0.2723  4.1800   0.0000
## patient_argument_type_cleanpronoun           1.3041     0.2779  4.6927   0.0000
## presentation_typeimmediate_after             0.6018     0.1903  3.1624   0.0016
## presentation_typesimultaneous                0.3410     0.1853  1.8404   0.0657
## test_mass_or_distributedmass                 0.4237     0.1129  3.7524   0.0002
## character_identificationyes                  0.1483     0.1187  1.2488   0.2118
## n_repetitions_sentence                       0.0127     0.0115  1.1045   0.2694
## practice_phaseyes                            0.0737     0.0919  0.8020   0.4226
## sentence_structuretransitive                -0.2035     0.2333 -0.8722   0.3831
## patient_argument_type_cleanvarying_patient  -0.2035     0.2333 -0.8722   0.3831
## mean_age                                     0.0001     0.0002  0.7232   0.4696
## stimuli_actorperson                         -0.0179     0.0357 -0.5001   0.6170
## test_methodpoint                             0.0104     0.0243  0.4292   0.6678
## n_repetitions_video                         -0.0012     0.0027 -0.4455   0.6560
##                                              ci.lb   ci.ub Importance
## intrcpt                                    -0.8946  0.2009     1.0000
## agent_argument_type_cleannoun_phrase       -0.0936  0.4839     1.0000
## agent_argument_type_cleanpronoun           -1.3381 -0.6409     1.0000
## agent_argument_type_cleanvarying_agent     -0.1311  0.5063     1.0000
## patient_argument_type_cleannoun            -0.3590  0.5932     1.0000
## patient_argument_type_cleannoun_phrase      0.6044  1.6717     1.0000
## patient_argument_type_cleanpronoun          0.7594  1.8488     1.0000
## presentation_typeimmediate_after            0.2288  0.9748     1.0000
## presentation_typesimultaneous              -0.0221  0.7041     1.0000
## test_mass_or_distributedmass                0.2024  0.6450     1.0000
## character_identificationyes                -0.0844  0.3810     0.7532
## n_repetitions_sentence                     -0.0098  0.0353     0.6923
## practice_phaseyes                          -0.1064  0.2539     0.5013
## sentence_structuretransitive               -0.6606  0.2537     0.5000
## patient_argument_type_cleanvarying_patient -0.6606  0.2537     0.5000
## mean_age                                   -0.0002  0.0005     0.4151
## stimuli_actorperson                        -0.0879  0.0522     0.1406
## test_methodpoint                           -0.0372  0.0580     0.0863
## n_repetitions_video                        -0.0065  0.0041     0.0388

take stimuli modality

res_stimuli_modality <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean  + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)
## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
## 
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 726.927294368649

## 
## After 100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Crit= 685.621375640315
## Mean crit= 704.902195771666

## 
## After 150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Crit= 679.326562070076
## Mean crit= 691.69364491043

## 
## After 200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Crit= 658.04629132771
## Mean crit= 680.112874528386

## 
## After 250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 654.840389646851
## Mean crit= 671.055451082595

## 
## After 300 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 666.406910711395

## 
## After 350 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 664.826888009878

## 
## After 400 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 662.026036119666

## 
## After 450 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 661.80561850372

## 
## After 500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed+practice_phase
## Crit= 643.215901075392
## Mean crit= 657.116876940897

## 
## After 550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464
## 
## After 600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464

## 
## After 650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464
## 
## After 700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464
## 
## After 750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.039344274024

## 
## After 800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042
## 
## After 850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042

## 
## After 900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042
## 
## After 950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042
## 
## After 1000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 649.027793085993

## 
## After 1050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 648.906804481044

## 
## After 1100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355
## 
## After 1150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355

## 
## After 1200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355
## 
## After 1250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355
## 
## After 1300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355
## 
## After 1350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.86694151453
## 
## After 1400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.86694151453

## 
## After 1450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.86694151453
## 
## After 1500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.460382494939

## 
## After 1550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 644.8481747198

## 
## After 1600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361
## 
## After 1650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361

## 
## After 1700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361
## 
## After 1750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361
## 
## After 1800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361
## 
## After 1850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361
## 
## After 1900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.984538021898
## 
## After 1950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.984538021898

## 
## After 2000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.984538021898
## 
## After 2050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.796141432037

## 
## After 2100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.666761153361

## 
## After 2150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268
## 
## After 2200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268

## 
## After 2250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268
## 
## After 2300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268
## 
## After 2350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268
## 
## After 2400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692
## 
## After 2450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692

## 
## After 2500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692
## 
## After 2550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692
## 
## After 2600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.463467797289

## 
## After 2650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282
## 
## After 2700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282

## 
## After 2750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282
## 
## After 2800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282
## 
## After 2850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.301836506431
## 
## After 2900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.301836506431

## 
## After 2950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875
## 
## After 3000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875

## 
## After 3050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875
## 
## After 3100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875
## 
## After 3150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.828104104437

## 
## After 3200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214
## 
## After 3250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214

## 
## After 3300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214
## 
## After 3350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214
## 
## After 3400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214
## 
## After 3450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584
## 
## After 3500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584

## 
## After 3550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584
## 
## After 3600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584
## 
## After 3650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584
## 
## After 3700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584
## 
## After 3750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289
## 
## After 3800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289

## 
## After 3850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289
## 
## After 3900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289
## 
## After 3950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289
## 
## After 4000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817
## 
## After 4050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817

## 
## After 4100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817
## 
## After 4150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817
## 
## After 4200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817
## 
## After 4250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.367357490081

## Completed.
print(res)
## Global model call: rma.mv(yi = d_calc, V = d_var_calc, mods = ~mean_age + agent_argument_type_clean + 
##     patient_argument_type_clean + stimuli_modality + stimuli_actor + 
##     presentation_type + test_mass_or_distributed + practice_phase + 
##     character_identification + n_repetitions_sentence + n_repetitions_video + 
##     test_method, data = ma_data, method = "ML")
## ---
## Model selection table 
##      (Int) agn_arg_typ_cln chr_idn    men_age  n_rpt_snt  n_rpt_vid
## 4028     +               +       +             2.482e-02 -1.557e-01
## 4026     +               +                     2.037e-02 -1.422e-01
## 4090     +               +                     2.110e-02 -1.083e-01
## 1980     +               +       +             2.196e-02 -1.757e-01
## 4092     +               +       +             2.443e-02 -1.322e-01
## 4032     +               +       + -6.528e-05  2.476e-02 -1.582e-01
## 2044     +               +       +             2.166e-02 -1.446e-01
## 2042     +               +                     1.755e-02 -1.181e-01
## 4018     +               +                               -1.402e-01
## 4082     +               +                               -1.086e-01
## 4030     +               +          9.070e-05  2.086e-02 -1.399e-01
## 4020     +               +       +                       -1.493e-01
## 1984     +               +       +  1.257e-04  2.250e-02 -1.680e-01
## 2034     +               +                               -1.167e-01
## 1972     +               +       +                       -1.667e-01
## 4094     +               +          9.039e-06  2.114e-02 -1.083e-01
## 1978     +               +                     1.600e-02 -1.632e-01
## 1982     +               +          2.699e-04  1.881e-02 -1.500e-01
## 1970     +               +                               -1.587e-01
## 4096     +               +       + -9.424e-05  2.431e-02 -1.341e-01
## 2046     +               +          1.798e-04  1.916e-02 -1.168e-01
## 2036     +               +       +                       -1.340e-01
## 4074     +               +                     2.118e-02           
## 4084     +               +       +                       -1.230e-01
## 2048     +               +       +  8.919e-05  2.207e-02 -1.414e-01
## 4022     +               +          4.295e-05            -1.391e-01
## 1974     +               +          2.049e-04            -1.481e-01
## 2038     +               +          1.164e-04            -1.158e-01
## 4086     +               +         -3.697e-05            -1.084e-01
## 4024     +               +       + -7.645e-05            -1.522e-01
## 1976     +               +       +  8.849e-05            -1.611e-01
## 4066     +               +                                         
## 4076     +               +       +             2.211e-02           
## 2040     +               +       +  4.932e-05            -1.322e-01
## 4078     +               +         -2.502e-06  2.117e-02           
## 4088     +               +       + -1.089e-04            -1.253e-01
## 2026     +               +                     1.710e-02           
## 3896     +               +       + -3.662e-04            -1.411e-01
## 2018     +               +                                         
## 3960     +               +       + -3.991e-04            -1.100e-01
## 2030     +               +          1.956e-04  1.886e-02           
## 3904     +               +       + -3.599e-04  1.036e-02 -1.309e-01
## 4070     +               +         -4.858e-05                      
## 4068     +               +       +                                 
## 3892     +               +       +                       -1.278e-01
## 4080     +               +       + -3.214e-05  2.206e-02           
## 2028     +               +       +             1.840e-02           
## 3968     +               +       + -3.936e-04  1.070e-02 -9.859e-02
## 2022     +               +          1.330e-04                      
## 3900     +               +       +             1.081e-02 -1.175e-01
## 2020     +               +       +                                 
## 3958     +               +         -3.513e-04            -7.368e-02
## 3956     +               +       +                       -1.029e-01
## 2032     +               +       +  1.801e-04  1.937e-02           
## 1844     +               +       +                       -1.350e-01
## 3964     +               +       +             1.110e-02 -9.120e-02
## 4072     +               +       + -4.922e-05                      
## 1908     +               +       +                       -1.003e-01
## 3942     +               +         -3.401e-04                      
## 3954     +               +                               -7.132e-02
## 3952     +               +       + -3.594e-04  1.459e-02           
## 2024     +               +       +  1.396e-04                      
## 3950     +               +         -3.314e-04  1.083e-02           
## 4010     +               +                     1.944e-02           
## 3966     +               +         -3.440e-04  7.079e-03 -6.339e-02
## 956      +               +       +             3.340e-02 -1.998e-01
## 3944     +               +       + -3.616e-04                      
## 3938     +               +                                         
## 1020     +               +       +             3.258e-02 -1.579e-01
## 3890     +               +                               -1.088e-01
## 1912     +               +       + -1.734e-04            -1.027e-01
## 1848     +               +       + -1.186e-04            -1.405e-01
## 3946     +               +                     1.131e-02           
## 3894     +               +         -2.707e-04            -1.164e-01
## 3962     +               +                     7.772e-03 -6.007e-02
## 3948     +               +       +             1.470e-02           
## 1852     +               +       +             3.135e-03 -1.325e-01
## 4012     +               +       +             2.202e-02           
## 1018     +               +                     2.831e-02 -1.293e-01
## 4002     +               +                                         
## 1916     +               +       +             4.282e-03 -9.552e-02
## 4014     +               +          1.907e-04  2.049e-02           
## 1906     +               +                               -6.356e-02
## 3940     +               +       +                                 
## 1890     +               +                                         
## 960      +               +       + -1.418e-04  3.194e-02 -2.067e-01
## 1024     +               +       + -1.809e-04  3.064e-02 -1.629e-01
## 3898     +               +                     5.905e-03 -1.019e-01
## 1892     +               +       +                                 
## 3004     +               +       +             3.310e-02 -2.004e-01
## 3902     +               +         -2.631e-04  5.115e-03 -1.103e-01
## 1920     +               +       + -1.619e-04  2.850e-03 -9.935e-02
## 1856     +               +       + -1.098e-04  2.061e-03 -1.384e-01
## 3068     +               +       +             3.203e-02 -1.587e-01
## 4006     +               +          1.432e-04                      
## 4016     +               +       +  1.263e-04  2.223e-02           
## 4004     +               +       +                                 
## 1022     +               +         -7.428e-05  2.721e-02 -1.294e-01
## 1910     +               +         -1.098e-04            -6.314e-02
## 3066     +               +                     2.811e-02 -1.295e-01
## 1894     +               +         -1.141e-04                      
## 1900     +               +       +             7.749e-03           
## 1914     +               +                     4.205e-04 -6.287e-02
## 1898     +               +                     3.983e-03           
## 1896     +               +       + -1.518e-04                      
## 954      +               +                     2.721e-02 -1.868e-01
## 3008     +               +       + -1.871e-04  3.271e-02 -2.063e-01
## 3072     +               +       + -2.290e-04  3.145e-02 -1.624e-01
## 1966     +               +          4.372e-04  1.775e-02           
## 1958     +               +          3.737e-04                      
## 4008     +               +       +  1.097e-04                      
## 1842     +               +                               -1.134e-01
## 1904     +               +       + -1.263e-04  6.740e-03           
## 1918     +               +         -1.133e-04 -7.283e-04 -6.431e-02
## 3070     +               +         -9.630e-05  2.757e-02 -1.288e-01
## 1902     +               +         -9.941e-05  3.047e-03           
## 1724     +               +       +             2.436e-02 -9.189e-02
## 3884     +               +       +             1.715e-02           
## 958      +               +          3.672e-05  2.778e-02 -1.854e-01
## 1968     +               +       +  3.909e-04  1.908e-02           
## 3002     +               +                     2.773e-02 -1.859e-01
## 1728     +               +       +  2.269e-04  2.526e-02 -8.047e-02
## 3888     +               +       + -2.298e-04  1.733e-02           
## 1002     +               +                     2.842e-02           
## 1960     +               +       +  3.499e-04                      
## 1850     +               +                    -3.580e-03 -1.172e-01
## 1954     +               +                                         
## 3772     +               +       +             2.547e-02 -8.128e-02
## 1010     +               +                               -1.299e-01
## 1846     +               +          1.805e-05            -1.128e-01
## 1788     +               +       +             2.437e-02 -9.598e-02
## 1962     +               +                     1.278e-02           
## 3876     +               +       +                                 
## 1964     +               +       +             1.667e-02           
## 3882     +               +                     1.245e-02           
## 1956     +               +       +                                 
## 1014     +               +         -2.104e-04            -1.300e-01
## 3874     +               +                                         
## 3006     +               +          2.942e-05  2.790e-02 -1.852e-01
## 3880     +               +       + -2.232e-04                      
## 1016     +               +       + -2.989e-04            -1.541e-01
## 3058     +               +                               -1.324e-01
## 1716     +               +       +                       -7.945e-02
## 1004     +               +       +             2.980e-02           
## 1792     +               +       +  2.352e-04  2.533e-02 -8.967e-02
## 1012     +               +       +                       -1.444e-01
## 3776     +               +       +  2.032e-04  2.563e-02 -7.728e-02
## 1006     +               +         -7.191e-05  2.736e-02           
## 948      +               +       +                       -1.918e-01
## 3050     +               +                     2.879e-02           
## 1854     +               +         -2.290e-06 -3.609e-03 -1.173e-01
## 3886     +               +         -1.693e-04  1.229e-02           
## 952      +               +       + -2.588e-04            -2.051e-01
## 3878     +               +         -1.755e-04                      
## 3836     +               +       +             2.558e-02 -8.925e-02
## 1772     +               +       +             2.180e-02           
## 1712     +               +       +  3.662e-04  2.212e-02           
## 946      +               +                               -1.837e-01
## 3060     +               +       +                       -1.500e-01
## 1710     +               +          4.796e-04  1.943e-02           
## 3756     +               +       +             2.359e-02           
## 1726     +               +          4.400e-04  2.028e-02 -4.725e-02
## 1776     +               +       +  2.803e-04  2.315e-02           
## 1720     +               +       +  1.886e-04            -6.957e-02
## 2996     +               +       +                       -1.984e-01
## 3062     +               +         -1.688e-04            -1.311e-01
## 1774     +               +          4.095e-04  2.019e-02           
## 3820     +               +       +             2.387e-02           
## 1008     +               +       + -1.091e-04  2.858e-02           
## 3764     +               +       +                       -7.422e-02
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## 999      +                       + -6.437e-04                      
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## 3198     +               +         -7.718e-07 -8.676e-04  7.620e-02
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## 320      +               +       + -2.427e-04  6.205e-03 -3.846e-02
## 292      +               +       +                                 
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## 2962     +               +                               -1.633e-01
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## 1947     +                       +             9.959e-03 -1.360e-01
## 945      +                                               -9.731e-02
## 916      +               +       +                       -1.667e-01
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## 1403     +                       +             1.879e-02  8.687e-02
## 918      +               +         -2.443e-05            -1.670e-01
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## 1949     +                          6.968e-05  9.433e-03 -1.264e-01
## 3455     +                       + -3.399e-04  1.469e-02  8.048e-02
## 3930     +               +                     8.243e-03 -6.337e-02
## 3936     +               +       + -3.682e-04  8.869e-03 -8.213e-02
## 943      +                       + -3.672e-04  2.214e-02           
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## 1011     +                       +                       -5.329e-02
## 2865     +                                               -1.198e-01
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## 290      +               +                                         
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## 3030     +               +         -2.191e-04            -1.218e-01
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## 3453     +                         -3.001e-04  1.179e-02  1.031e-01
## 1771     +                       +             2.199e-02           
## 3906     +               +                                         
## 1571     +                       +                                 
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## 947      +                       +                       -1.005e-01
## 3924     +               +       +                       -8.418e-02
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## 984      +               +       + -9.900e-05            -1.220e-01
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## 3447     +                       + -3.697e-04             6.078e-02
## 2913     +                                                         
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## 3870     +               +         -2.526e-04  6.325e-03 -1.113e-01
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## 3747     +                       +                                 
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## 1659     +                       +             1.685e-02  2.774e-02
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## 3683     +                       +                                 
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## 3451     +                       +             1.613e-02  7.760e-02
## 3635     +                       +                       -5.613e-03
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## 813      +                         -3.267e-04  1.424e-02           
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## 1525     +                         -2.825e-04             9.755e-02
## 1985     +                                                         
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## 3932     +               +       +             9.112e-03 -7.338e-02
## 3970     +               +                                         
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## 306      +               +                               -1.749e-02
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## 920      +               +       + -6.294e-05            -1.701e-01
## 3969     +                                                         
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## 3441     +                                                7.146e-02
## 1811     +                       +                       -1.448e-01
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## 972      +               +       +             1.803e-02           
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## 1587     +                       +                        1.385e-02
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## 2015     +                       +  9.989e-06  9.078e-03 -9.923e-02
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## 3916     +               +       +             1.235e-02           
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## 1987     +                       +                                 
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## 3022     +               +         -1.887e-04  2.233e-02           
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## 962      +               +                                         
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## 805      +                         -4.471e-04                      
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## 3427     +                       +                                 
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## 3745     +                                                         
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## 2072     +               +       + -1.980e-04            -1.853e-02
## 2132     +               +       +                        4.014e-03
## 2064     +               +       + -1.940e-04  5.247e-03           
## 32       +               +       + -1.441e-04  1.968e-03 -1.815e-02
## 2067     +                       +                       -3.547e-02
## 540      +               +       +             3.499e-03 -2.654e-02
## 583      +                       + -1.674e-04                      
## 2059     +                       +             1.157e-02           
## 31       +                       + -1.243e-04  2.633e-03 -4.075e-02
## 2197     +                         -3.755e-05            -2.267e-02
## 539      +                       +             6.552e-03 -4.329e-02
## 2135     +                       + -2.952e-04            -1.772e-02
## 2568     +               +       + -2.009e-04                      
## 2580     +               +       +                       -3.125e-02
## 2695     +                       + -1.518e-04                      
## 2632     +               +       + -2.177e-04                      
## 733      +                         -3.432e-05  1.494e-02 -1.803e-03
## 2765     +                         -3.707e-05  1.503e-02           
## 528      +               +       + -1.207e-04  4.340e-03           
## 2115     +                       +                                 
## 2775     +                       + -2.267e-04            -5.349e-02
## 579      +                       +                                 
## 2777     +                                     1.516e-02 -2.417e-03
## 91       +                       +             7.255e-03 -1.400e-02
## 269      +                          7.082e-05  3.407e-03           
## 592      +               +       + -1.673e-04  2.262e-03           
## 600      +               +       + -1.783e-04            -1.140e-02
## 11       +                       +             7.045e-03           
## 2269     +                         -4.301e-05  1.504e-02  5.099e-03
## 2123     +                       +             9.549e-03           
## 2079     +                       + -2.552e-04  6.380e-03 -2.570e-02
## 2128     +               +       + -2.091e-04  2.764e-03           
## 2631     +                       + -3.105e-04                      
## 2136     +               +       + -2.110e-04             4.831e-03
## 587      +                       +             7.969e-03           
## 599      +                       + -1.824e-04            -4.351e-02
## 96       +               +       + -1.659e-04  2.162e-03  6.436e-03
## 2584     +               +       + -2.157e-04            -3.358e-02
## 2757     +                         -6.274e-05                      
## 543      +                       + -1.457e-04  2.455e-03 -5.718e-02
## 725      +                         -9.178e-05            -4.078e-03
## 2261     +                         -6.560e-05            -1.328e-03
## 2769     +                                               -1.016e-02
## 2075     +                       +             7.974e-03 -2.472e-02
## 2693     +                         -2.720e-05                      
## 95       +                       + -1.513e-04  3.221e-03 -2.153e-02
## 2572     +               +       +             5.990e-03           
## 544      +               +       + -1.595e-04  1.522e-03 -3.341e-02
## 2717     +                         -9.546e-06  1.520e-02 -2.315e-02
## 2076     +               +       +             3.616e-03 -1.356e-02
## 2051     +                       +                                 
## 2334     +               +         -1.421e-04  1.752e-03 -4.459e-03
## 2591     +                       + -2.814e-04  6.310e-03 -4.234e-02
## 2579     +                       +                       -4.857e-02
## 595      +                       +                       -3.700e-02
## 3153     +                                                5.579e-02
## 2639     +                       + -2.865e-04  8.321e-03           
## 2143     +                       + -2.773e-04  6.836e-03 -7.726e-03
## 2131     +                       +                       -2.335e-02
## 2575     +                       + -2.572e-04  1.085e-02           
## 7        +                       + -4.389e-05                      
## 515      +                       +                                 
## 2709     +                         -3.034e-05            -3.141e-02
## 2647     +                       + -3.058e-04            -3.790e-02
## 591      +                       + -1.276e-04  4.784e-03           
## 2636     +               +       +             3.667e-03           
## 604      +               +       +             3.892e-03 -4.702e-03
## 2576     +               +       + -2.018e-04  6.050e-03           
## 2644     +               +       +                       -9.944e-03
## 2080     +               +       + -1.969e-04  3.477e-03 -1.441e-02
## 2567     +                       + -2.830e-04                      
## 2140     +               +       +             3.582e-03  8.223e-03
## 603      +                       +             7.100e-03 -2.988e-02
## 2571     +                       +             1.201e-02           
## 2587     +                       +             8.049e-03 -3.787e-02
## 3089     +                                                3.161e-02
## 2588     +               +       +             3.277e-03 -2.714e-02
## 523      +                       +             6.860e-03           
## 2627     +                       +                                 
## 2640     +               +       + -2.169e-04  3.565e-03           
## 2139     +                       +             8.439e-03 -1.059e-02
## 15       +                       +  5.879e-06  7.200e-03           
## 3073     +                                                         
## 2635     +                       +             9.955e-03           
## 2648     +               +       + -2.191e-04            -1.138e-02
## 2781     +                         -3.635e-05  1.498e-02 -1.504e-03
## 608      +               +       + -1.702e-04  1.838e-03 -8.984e-03
## 607      +                       + -1.570e-04  2.894e-03 -3.970e-02
## 1029     +                          2.660e-04                      
## 3665     +                                                6.720e-02
## 2144     +               +       + -2.099e-04  3.432e-03  8.860e-03
## 3074     +               +                                         
## 3090     +               +                                3.247e-02
## 2592     +               +       + -2.145e-04  3.086e-03 -2.970e-02
## 2773     +                         -5.818e-05            -8.558e-03
## 2655     +                       + -2.881e-04  6.601e-03 -2.738e-02
## 2563     +                       +                                 
## 3157     +                          8.168e-05             5.371e-02
## 2643     +                       +                       -3.983e-02
## 3081     +                                    -6.895e-03           
## 1030     +               +          2.470e-04                      
## 519      +                       + -5.069e-05                      
## 1109     +                          2.360e-04             4.004e-02
## 3161     +                                    -1.515e-03  5.285e-02
## 3154     +               +                                5.314e-02
## 3093     +                          1.355e-04             3.093e-02
## 3077     +                          1.434e-04                      
## 1037     +                          2.145e-04 -6.623e-03           
## 1097     +                                    -1.068e-02           
## 2652     +               +       +             3.381e-03 -5.498e-03
## 3078     +               +          1.545e-04                      
## 3082     +               +                    -6.412e-03           
## 1093     +                          2.153e-04                      
## 3137     +                                                         
## 1045     +                          3.044e-04             1.476e-02
## 3097     +                                    -3.280e-03  2.622e-02
## 2651     +                       +             8.300e-03 -2.646e-02
## 3094     +               +          1.498e-04             3.206e-02
## 1026     +               +                                         
## 1046     +               +          2.645e-04             2.387e-02
## 3601     +                                                3.366e-02
## 1034     +               +                    -9.276e-03           
## 1038     +               +          2.127e-04 -7.098e-03           
## 527      +                       + -9.965e-07  6.832e-03           
## 3585     +                                                         
## 3666     +               +                                6.899e-02
## 3602     +               +                                3.760e-02
## 3145     +                                    -7.661e-03           
## 2656     +               +       + -2.179e-04  3.191e-03 -7.180e-03
## 1621     +                          2.041e-04             5.344e-02
## 1106     +               +                                4.984e-02
## 3669     +                          6.049e-05             6.478e-02
## 1541     +                          2.689e-04                      
## 1110     +               +          2.165e-04             4.677e-02
## 1101     +                          1.465e-04 -7.495e-03           
## 3085     +                          1.111e-04 -5.882e-03           
## 3673     +                                    -2.975e-04  6.651e-02
## 3098     +               +                    -2.396e-03  2.891e-02
## 3138     +               +                                         
## 3586     +               +                                         
## 1618     +               +                                7.017e-02
## 1113     +                                    -9.129e-03  2.448e-02
## 1117     +                          1.935e-04 -4.304e-03  3.421e-02
## 3158     +               +          1.205e-04             5.079e-02
## 3593     +                                    -6.825e-03           
## 3165     +                          7.816e-05 -7.668e-04  5.231e-02
## 1094     +               +          2.352e-04                      
## 1617     +                                                5.638e-02
## 1105     +                                                3.484e-02
## 1542     +               +          2.434e-04                      
## 1033     +                                    -1.208e-02           
## 3141     +                          1.313e-04                      
## 1042     +               +                                1.948e-02
## 1089     +                                                         
## 1053     +                          2.454e-04 -5.570e-03  8.703e-03
## 3086     +               +          1.394e-04 -5.769e-03           
## 3589     +                          1.469e-04                      
## 1098     +               +                    -1.012e-02           
## 3101     +                          1.258e-04 -1.910e-03  2.784e-02
## 3605     +                          1.332e-04             3.239e-02
## 3162     +               +                    -2.118e-03  4.985e-02
## 1549     +                          2.161e-04 -6.614e-03           
## 1622     +               +          1.827e-04             6.400e-02
## 1090     +               +                                         
## 1114     +               +                    -6.839e-03  3.992e-02
## 1609     +                                    -1.052e-02           
## 1054     +               +          2.360e-04 -4.970e-03  1.771e-02
## 1558     +               +          2.547e-04             2.914e-02
## 3606     +               +          1.429e-04             3.665e-02
## 1625     +                                    -7.226e-03  4.272e-02
## 3146     +               +                    -7.047e-03           
## 3649     +                                                         
## 1557     +                          2.994e-04             1.707e-02
## 1538     +               +                                         
## 1605     +                          2.185e-04                      
## 3609     +                                    -3.088e-03  2.810e-02
## 3590     +               +          1.542e-04                      
## 3142     +               +          1.545e-04                      
## 3594     +               +                    -6.440e-03           
## 1102     +               +          1.880e-04 -7.848e-03           
## 1050     +               +                    -8.199e-03  1.010e-02
## 1546     +               +                    -9.236e-03           
## 3102     +               +          1.459e-04 -1.617e-03  2.967e-02
## 3149     +                          8.904e-05 -6.737e-03           
## 3670     +               +          9.733e-05             6.589e-02
## 1550     +               +          2.086e-04 -7.120e-03           
## 1629     +                          1.751e-04 -3.261e-03  4.769e-02
## 1118     +               +          1.921e-04 -4.460e-03  4.064e-02
## 1626     +               +                    -4.949e-03  6.078e-02
## 3657     +                                    -7.599e-03           
## 3610     +               +                    -1.735e-03  3.475e-02
## 3674     +               +                    -7.638e-04  6.756e-02
## 3597     +                          1.147e-04 -5.761e-03           
## 1613     +                          1.483e-04 -7.484e-03           
## 3677     +                          6.134e-05  2.147e-04  6.524e-02
## 1049     +                                    -1.245e-02 -1.197e-02
## 1554     +               +                                2.659e-02
## 1545     +                                    -1.163e-02           
## 3650     +               +                                         
## 1601     +                                                         
## 3166     +               +          1.169e-04 -1.520e-03  4.850e-02
## 3653     +                          1.351e-04                      
## 1606     +               +          2.314e-04                      
## 1565     +                          2.439e-04 -5.424e-03  1.024e-02
## 1610     +               +                    -1.007e-02           
## 3150     +               +          1.336e-04 -6.211e-03           
## 3613     +                          1.245e-04 -1.775e-03  2.928e-02
## 1602     +               +                                         
## 3598     +               +          1.387e-04 -5.786e-03           
## 1630     +               +          1.679e-04 -3.128e-03  5.856e-02
## 1566     +               +          2.308e-04 -4.407e-03  2.293e-02
## 1562     +               +                    -7.444e-03  1.652e-02
## 1025     +                                                         
## 3658     +               +                    -7.092e-03           
## 3614     +               +          1.406e-04 -1.045e-03  3.496e-02
## 1614     +               +          1.836e-04 -7.876e-03           
## 3654     +               +          1.542e-04                      
## 3661     +                          9.248e-05 -6.617e-03           
## 3678     +               +          9.664e-05 -3.620e-04  6.524e-02
## 1561     +                                    -1.211e-02 -8.960e-03
## 1537     +                                                         
## 65       +                                                         
## 1041     +                                               -8.511e-03
## 3662     +               +          1.326e-04 -6.242e-03           
## 594      +               +                                6.909e-02
## 577      +                                                         
## 593      +                                                3.828e-02
## 2        +               +                                         
## 82       +               +                                4.508e-02
## 73       +                                    -3.510e-03           
## 81       +                                                1.535e-02
## 1553     +                                               -1.344e-03
## 2113     +                                                         
## 69       +                          2.255e-05                      
## 2049     +                                                         
## 66       +               +                                         
## 10       +               +                    -5.666e-03           
## 585      +                                    -3.430e-03           
## 1        +                                                         
## 514      +               +                                         
## 74       +               +                    -7.072e-03           
## 2625     +                                                         
## 513      +                                                         
## 2129     +                                                1.803e-02
## 598      +               +         -3.247e-05             7.023e-02
## 602      +               +                    -1.595e-03  6.605e-02
## 2641     +                                                3.861e-02
## 2642     +               +                                6.917e-02
## 581      +                          9.271e-06                      
## 2561     +                                                         
## 18       +               +                                9.858e-03
## 597      +                         -1.684e-05             3.914e-02
## 601      +                                    -3.734e-04  3.742e-02
## 5        +                          1.066e-04                      
## 90       +               +                    -3.828e-03  3.939e-02
## 89       +                                    -2.618e-03  1.122e-02
## 6        +               +          4.442e-05                      
## 2050     +               +                                         
## 2121     +                                    -2.641e-03           
## 77       +                         -2.258e-05 -4.180e-03           
## 85       +                          1.807e-05             1.506e-02
## 2117     +                         -4.152e-05                      
## 2130     +               +                                4.513e-02
## 86       +               +         -1.839e-06             4.511e-02
## 578      +               +                                         
## 17       +                                               -1.738e-02
## 2065     +                                               -5.194e-03
## 2053     +                         -2.834e-05                      
## 2057     +                                    -5.500e-04           
## 9        +                                    -4.709e-03           
## 70       +               +          1.818e-05                      
## 2114     +               +                                         
## 517      +                          8.490e-05                      
## 522      +               +                    -5.682e-03           
## 521      +                                    -4.450e-03           
## 530      +               +                                1.862e-02
## 25       +                                    -5.832e-03 -2.063e-02
## 586      +               +                    -7.058e-03           
## 589      +                         -4.214e-05 -4.675e-03           
## 2645     +                         -1.047e-04             4.455e-02
## 21       +                          8.758e-05            -1.273e-02
## 26       +               +                    -5.275e-03  3.512e-03
## 14       +               +          1.468e-05 -5.468e-03           
## 2633     +                                    -3.363e-03           
## 2058     +               +                    -5.579e-03           
## 2133     +                         -7.813e-05             2.155e-02
## 529      +                                               -8.194e-03
## 2122     +               +                    -8.076e-03           
## 518      +               +          3.661e-05                      
## 2562     +               +                                         
## 2629     +                         -3.604e-05                      
## 78       +               +         -2.801e-05 -7.498e-03           
## 2137     +                                    -2.781e-04  1.747e-02
## 2649     +                                     1.687e-03  4.266e-02
## 2066     +               +                                1.130e-02
## 2569     +                                    -1.278e-03           
## 13       +                          8.974e-05 -1.807e-03           
## 2565     +                         -2.274e-05                      
## 22       +               +          4.686e-05             1.016e-02
## 2577     +                                                2.221e-03
## 606      +               +         -4.392e-05 -2.236e-03  6.637e-02
## 2650     +               +                    -2.188e-03  6.510e-02
## 2125     +                         -6.855e-05 -3.567e-03           
## 2646     +               +         -3.711e-05             7.035e-02
## 605      +                         -2.955e-05 -1.299e-03  3.678e-02
## 93       +                         -1.371e-05 -3.063e-03  1.074e-02
## 2054     +               +          3.121e-05                      
## 94       +               +         -2.525e-05 -4.218e-03  3.931e-02
## 2138     +               +                    -4.307e-03  3.856e-02
## 582      +               +          1.114e-05                      
## 2073     +                                    -2.021e-03 -8.655e-03
## 2626     +               +                                         
## 2134     +               +         -1.110e-05             4.538e-02
## 2069     +                         -2.172e-05            -4.664e-03
## 2061     +                         -3.548e-05 -9.866e-04           
## 537      +                                    -5.222e-03 -1.268e-02
## 525      +                          6.052e-05 -2.521e-03           
## 533      +                          8.053e-05            -4.761e-03
## 538      +               +                    -4.286e-03  1.260e-02
## 2118     +               +          2.263e-05                      
## 29       +                          3.871e-05 -4.426e-03 -1.779e-02
## 2578     +               +                                1.974e-02
## 2570     +               +                    -5.784e-03           
## 526      +               +          5.888e-06 -5.602e-03           
## 534      +               +          3.742e-05             1.867e-02
## 2634     +               +                    -8.269e-03           
## 2637     +                         -6.783e-05 -4.277e-03           
## 590      +               +         -3.595e-05 -7.604e-03           
## 2653     +                         -1.017e-04  7.253e-04  4.612e-02
## 30       +               +          1.831e-05 -4.975e-03  3.991e-03
## 2074     +               +                    -4.979e-03  4.245e-03
## 2141     +                         -8.321e-05 -1.126e-03  1.951e-02
## 2062     +               +          1.653e-05 -5.498e-03           
## 2566     +               +          2.833e-05                      
## 2126     +               +         -1.192e-06 -8.083e-03           
## 2573     +                         -3.481e-05 -1.705e-03           
## 2585     +                                    -1.319e-03 -2.677e-04
## 2581     +                         -2.643e-05             2.933e-03
## 2070     +               +          2.540e-05             1.106e-02
## 2654     +               +         -4.060e-05 -2.329e-03  6.612e-02
## 2142     +               +         -1.919e-05 -4.387e-03  3.888e-02
## 2077     +                         -3.369e-05 -2.409e-03 -8.499e-03
## 541      +                          3.923e-05 -3.795e-03 -9.782e-03
## 2630     +               +          1.990e-05                      
## 2586     +               +                    -3.939e-03  1.347e-02
## 542      +               +          1.499e-05 -4.044e-03  1.296e-02
## 2582     +               +          1.668e-05             1.953e-02
## 2574     +               +          1.292e-05 -5.719e-03           
## 2638     +               +         -4.741e-06 -8.297e-03           
## 2078     +               +          1.590e-05 -4.908e-03  4.191e-03
## 2589     +                         -3.479e-05 -1.717e-03 -8.192e-05
## 2590     +               +          9.827e-06 -3.898e-03  1.341e-02
##      ptn_arg_typ_cln prc_phs prs_typ stm_act stm_mdl tst_mss_or_dst tst_mth df
## 4028               +               +       +       +              +       + 17
## 4026               +               +       +       +              +       + 16
## 4090               +       +       +       +       +              +       + 17
## 1980               +               +       +       +              +         16
## 4092               +       +       +       +       +              +       + 18
## 4032               +               +       +       +              +       + 18
## 2044               +       +       +       +       +              +         17
## 2042               +       +       +       +       +              +         16
## 4018               +               +       +       +              +       + 15
## 4082               +       +       +       +       +              +       + 16
## 4030               +               +       +       +              +       + 17
## 4020               +               +       +       +              +       + 16
## 1984               +               +       +       +              +         17
## 2034               +       +       +       +       +              +         15
## 1972               +               +       +       +              +         15
## 4094               +       +       +       +       +              +       + 18
## 1978               +               +       +       +              +         15
## 1982               +               +       +       +              +         16
## 1970               +               +       +       +              +         14
## 4096               +       +       +       +       +              +       + 19
## 2046               +       +       +       +       +              +         17
## 2036               +       +       +       +       +              +         16
## 4074               +       +       +       +       +              +       + 16
## 4084               +       +       +       +       +              +       + 17
## 2048               +       +       +       +       +              +         18
## 4022               +               +       +       +              +       + 16
## 1974               +               +       +       +              +         15
## 2038               +       +       +       +       +              +         16
## 4086               +       +       +       +       +              +       + 17
## 4024               +               +       +       +              +       + 17
## 1976               +               +       +       +              +         16
## 4066               +       +       +       +       +              +       + 15
## 4076               +       +       +       +       +              +       + 17
## 2040               +       +       +       +       +              +         17
## 4078               +       +       +       +       +              +       + 17
## 4088               +       +       +       +       +              +       + 18
## 2026               +       +       +       +       +              +         15
## 3896               +                       +       +              +       + 15
## 2018               +       +       +       +       +              +         14
## 3960               +       +               +       +              +       + 16
## 2030               +       +       +       +       +              +         16
## 3904               +                       +       +              +       + 16
## 4070               +       +       +       +       +              +       + 16
## 4068               +       +       +       +       +              +       + 16
## 3892               +                       +       +              +       + 14
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## 2022               +       +       +       +       +              +         15
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## 3956               +       +               +       +              +       + 15
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## 3952               +       +               +       +              +       + 16
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## 3950               +       +               +       +              +       + 15
## 4010               +               +       +       +              +       + 15
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## 956                +               +       +       +                        15
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## 3938               +       +               +       +              +       + 13
## 1020               +       +       +       +       +                        16
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## 3962               +       +               +       +              +       + 15
## 3948               +       +               +       +              +       + 15
## 1852               +                       +       +              +         14
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## 1018               +       +       +       +       +                        15
## 4002               +               +       +       +              +       + 14
## 1916               +       +               +       +              +         15
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## 1906               +       +               +       +              +         13
## 3940               +       +               +       +              +       + 14
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## 960                +               +       +       +                        16
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## 3004               +               +       +       +                      + 16
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## 4004               +               +       +       +              +       + 15
## 1022               +       +       +       +       +                        16
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## 954                +               +       +       +                        14
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## 1724               +               +               +              +         15
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## 958                +               +       +       +                        15
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## 1850               +                       +       +              +         13
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## 1962               +               +       +       +              +         14
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## 1956               +               +       +       +              +         14
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## 3874               +                       +       +              +       + 12
## 3006               +               +       +       +                      + 16
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## 1016               +       +       +       +       +                        16
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## 1004               +       +       +       +       +                        15
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## 1012               +       +       +       +       +                        15
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## 1006               +       +       +       +       +                        15
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## 1854               +                       +       +              +         14
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## 952                +               +       +       +                        15
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## 1772               +       +       +               +              +         15
## 1712               +               +               +              +         15
## 946                +               +       +       +                        13
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## 1720               +               +               +              +         15
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## 1008               +       +       +       +       +                        16
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## 3750               +               +               +              +       + 14
## 994                +       +       +       +       +                        13
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## 1722               +               +               +              +         14
## 1832               +                       +       +              +         13
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## 1826               +                       +       +              +         11
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## 998                +       +       +       +       +                        14
## 3818               +       +       +               +              +       + 15
## 3838               +       +       +               +              +       + 17
## 3814               +       +       +               +              +       + 15
## 1840               +                       +       +              +         14
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## 3770               +               +               +              +       + 15
## 3832               +       +       +               +              +       + 17
## 1706               +               +               +              +         13
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## 3816               +       +       +               +              +       + 16
## 3042               +       +       +       +       +                      + 14
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## 3762               +               +               +              +       + 14
## 888                +       +               +       +                        14
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## 1830               +                       +       +              +         12
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## 3830               +       +       +               +              +       + 16
## 1260               +       +       +                              +         14
## 3834               +       +       +               +              +       + 16
## 1000               +       +       +       +       +                        15
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## 3044               +       +       +       +       +                      + 15
## 896                +       +               +       +                        15
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## 2944               +       +               +       +                      + 16
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## 764                +       +       +               +                        15
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## 1588               +                               +              +         12
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## 3566               +       +       +       +                      +       + 16
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## 3636               +                               +              +       + 13
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## 3306               +       +       +                              +       + 14
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## 3252               +               +                              +       + 14
## 748                +       +       +               +                        14
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## 3262               +               +                              +       + 15
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## 3326               +       +       +                              +       + 16
## 1596               +                               +              +         13
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## 878                +       +               +       +                        13
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## 3941               +       +               +       +              +       + 11
## 1652               +       +                       +              +         13
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## 894                +       +               +       +                        14
## 3254               +               +                              +       + 14
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## 1855               +                       +       +              +         12
## 1528               +       +       +       +                      +         16
## 1847               +                       +       +              +         11
## 884                +       +               +       +                        13
## 1060               +                                              +         10
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## 3498               +               +       +                      +       + 14
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## 3496               +               +       +                      +       + 15
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## 3560               +       +       +       +                      +       + 16
## 3256               +               +                              +       + 15
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## 3632               +                               +              +       + 14
## 3314               +       +       +                              +       + 14
## 3640               +                               +              +       + 14
## 3574               +       +       +       +                      +       + 16
## 2926               +       +               +       +                      + 14
## 1210               +               +                              +         13
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## 1316               +                       +                      +         11
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## 2942               +       +               +       +                      + 15
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## 1458               +               +       +                      +         13
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## 1584               +                               +              +         13
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## 1396               +       +               +                      +         13
## 3250               +               +                              +       + 13
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## 1124               +       +                                      +         11
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## 3108               +                                              +       + 11
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## 3518               +               +       +                      +       + 16
## 752                +       +       +               +                        15
## 2932               +       +               +       +                      + 14
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## 3258               +               +                              +       + 14
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## 4069               +       +       +       +       +              +       + 13
## 3428               +       +               +                      +       + 13
## 3943               +       +               +       +              +       + 12
## 1897               +       +               +       +              +         10
## 1466               +               +       +                      +         14
## 820                +                       +       +                        12
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## 1656               +       +                       +              +         14
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## 1068               +                                              +         11
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## 1076               +                                              +         11
## 876                +       +               +       +                        13
## 1064               +                                              +         11
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## 2940               +       +               +       +                      + 15
## 1324               +                       +                      +         12
## 828                +                       +       +                        13
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## 1332               +                       +                      +         12
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## 236                +       +       +                                        13
## 2740               +               +               +                      + 14
## 3704               +       +                       +              +       + 15
## 1899               +       +               +       +              +         11
## 1320               +                       +                      +         12
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## 4093               +       +       +       +       +              +       + 15
## 866                +       +               +       +                        11
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## 3708               +       +                       +              +       + 15
## 746                +       +       +               +                        13
## 3116               +                                              +       + 12
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## 3172               +       +                                      +       + 12
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## 2045               +       +       +       +       +              +         14
## 874                +       +               +       +                        12
## 4071               +       +       +       +       +              +       + 14
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## 3112               +                                              +       + 12
## 4031               +               +       +       +              +       + 15
## 3432               +       +               +                      +       + 14
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## 3436               +       +               +                      +       + 14
## 3124               +                                              +       + 12
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## 3380               +                       +                      +       + 13
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## 2868               +                       +       +                      + 13
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## 890                +       +               +       +                        13
## 940                +               +       +       +                        14
## 490                +       +       +       +                                13
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## 698                +               +               +                        13
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## 3452               +       +               +                      +       + 15
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## 938                +               +       +       +                        13
## 750                +       +       +               +                        14
## 1328               +                       +                      +         13
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## 3863                                       +       +              +       +  8
## 1017               +       +       +       +       +                        12
## 986                        +       +       +       +                        11
## 52                 +                                                        10
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## 2084               +                                                      + 10
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## 2088               +                                                      + 11
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## 2668               +       +                       +                      + 13
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## 2368               +                       +                              + 14
## 116                +       +                                                11
## 1575               +                               +              +          9
## 3871                                       +       +              +       +  9
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## 60                 +                                                        11
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## 1003               +       +       +       +       +                        12
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## 2620               +                               +                      + 13
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## 2600               +                               +                      + 12
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## 3034                       +       +       +       +                      + 12
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## 955                +               +       +       +                        12
## 3992                               +       +       +              +       + 13
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## 2176               +       +                                              + 14
## 4034                       +       +       +       +              +       + 11
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## 1019               +       +       +       +       +                        13
## 3929                       +               +       +              +       +  8
## 2172               +       +                                              + 13
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## 2863               +                       +       +                      + 11
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## 3921                       +               +       +              +       +  7
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## 2108               +                                                      + 12
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## 4043                       +       +       +       +              +       + 10
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## 953                +               +       +       +                        11
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## 636                +       +                       +                        13
## 2112               +                                                      + 13
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## 4051                       +       +       +       +              +       + 10
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## 4035                       +       +       +       +              +       +  9
## 1711               +               +               +              +         12
## 3869                                       +       +              +       +  8
## 1937                               +       +       +              +          7
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## 1647               +       +                       +              +         11
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## 4039                       +       +       +       +              +       + 10
## 3859                                       +       +              +       +  7
## 3865                                       +       +              +       +  7
## 926                                +       +       +                        11
## 1952                               +       +       +              +         13
## 825                +                       +       +                         9
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## 1009               +       +       +       +       +                        11
## 3001               +               +       +       +                      + 12
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## 2974                               +       +       +                      + 12
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## 2867               +                       +       +                      + 10
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## 3905                       +               +       +              +       +  6
## 2873               +                       +       +                      + 10
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## 945                +               +       +       +                        10
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## 290                +                       +                                 9
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## 314                +                       +                                11
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## 359                +       +               +                                 9
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## 1823                                       +       +              +          8
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## 2654                       +                       +                      + 10
## 2142                       +                                              +  9
## 2077                                                                      +  5
## 541                                                +                         5
## 2630                       +                       +                      +  8
## 2586                                               +                      +  8
## 542                                                +                         8
## 2582                                               +                      +  8
## 2574                                               +                      +  8
## 2638                       +                       +                      +  9
## 2078                                                                      +  8
## 2589                                               +                      +  6
## 2590                                               +                      +  9
##        logLik  AICc  delta weight
## 4028 -292.796 626.6   0.00  0.166
## 4026 -294.767 627.7   1.09  0.096
## 4090 -293.488 628.0   1.38  0.083
## 1980 -294.968 628.1   1.49  0.079
## 4092 -292.379 628.7   2.08  0.059
## 4032 -292.748 629.4   2.82  0.041
## 2044 -294.288 629.6   2.98  0.037
## 2042 -295.750 629.7   3.06  0.036
## 4018 -297.159 629.7   3.08  0.036
## 4082 -296.048 630.3   3.65  0.027
## 4030 -294.657 630.3   3.72  0.026
## 4020 -296.155 630.5   3.86  0.024
## 1984 -294.740 630.5   3.89  0.024
## 2034 -297.580 630.6   3.93  0.023
## 1972 -297.651 630.7   4.07  0.022
## 4094 -293.487 630.9   4.30  0.019
## 1978 -297.780 631.0   4.33  0.019
## 1982 -296.517 631.2   4.59  0.017
## 1970 -299.313 631.3   4.66  0.016
## 4096 -292.280 631.5   4.87  0.015
## 2046 -295.245 631.5   4.90  0.014
## 2036 -296.897 632.0   5.35  0.011
## 4074 -296.901 632.0   5.36  0.011
## 4084 -295.625 632.3   5.66  0.010
## 2048 -294.177 632.3   5.68  0.010
## 4022 -297.134 632.5   5.82  0.009
## 1974 -298.558 632.5   5.88  0.009
## 2038 -297.362 632.9   6.28  0.007
## 4086 -296.031 633.1   6.47  0.007
## 4024 -296.088 633.2   6.58  0.006
## 1976 -297.538 633.3   6.63  0.006
## 4066 -299.482 634.4   7.73  0.003
## 4076 -296.803 634.6   8.01  0.003
## 2040 -296.863 634.8   8.13  0.003
## 4078 -296.901 634.8   8.21  0.003
## 4088 -295.492 634.9   8.31  0.003
## 2026 -299.861 635.1   8.49  0.002
## 3896 -300.149 635.7   9.06  0.002
## 2018 -301.600 635.9   9.24  0.002
## 3960 -299.213 636.6   9.98  0.001
## 2030 -299.264 636.7  10.08  0.001
## 3904 -299.275 636.7  10.10  0.001
## 4070 -299.452 637.1  10.46  0.001
## 4068 -299.479 637.1  10.51  0.001
## 3892 -302.380 637.4  10.80  0.001
## 4080 -296.792 637.5  10.91  0.001
## 2028 -299.687 637.6  10.93  0.001
## 3968 -298.282 637.6  10.97  0.001
## 2022 -301.315 638.0  11.40  0.001
## 3900 -301.429 638.3  11.62  0.000
## 2020 -301.590 638.6  11.95  0.000
## 3958 -301.778 638.9  12.32  0.000
## 3956 -301.813 639.0  12.39  0.000
## 2032 -299.224 639.5  12.86  0.000
## 1844 -304.852 639.7  13.08  0.000
## 3964 -300.810 639.8  13.18  0.000
## 4072 -299.452 639.9  13.31  0.000
## 1908 -303.769 640.2  13.58  0.000
## 3942 -303.816 640.3  13.67  0.000
## 3954 -303.823 640.3  13.69  0.000
## 3952 -301.212 640.6  13.98  0.000
## 2024 -301.309 640.8  14.17  0.000
## 3950 -302.735 640.9  14.24  0.000
## 4010 -302.744 640.9  14.25  0.000
## 3966 -301.356 640.9  14.27  0.000
## 956  -302.906 641.2  14.58  0.000
## 3944 -303.019 641.4  14.80  0.000
## 3938 -305.734 641.5  14.84  0.000
## 1020 -301.717 641.6  14.99  0.000
## 3890 -305.828 641.7  15.03  0.000
## 1912 -303.147 641.7  15.06  0.000
## 1848 -304.547 641.8  15.13  0.000
## 3946 -304.554 641.8  15.15  0.000
## 3894 -304.564 641.8  15.17  0.000
## 3962 -303.313 642.0  15.39  0.000
## 3948 -303.334 642.1  15.43  0.000
## 1852 -304.758 642.2  15.56  0.000
## 4012 -302.027 642.2  15.61  0.000
## 1018 -303.443 642.3  15.65  0.000
## 4002 -304.924 642.5  15.89  0.000
## 1916 -303.597 642.6  15.96  0.000
## 4014 -302.250 642.7  16.05  0.000
## 1906 -306.381 642.8  16.13  0.000
## 3940 -305.168 643.0  16.37  0.000
## 1890 -307.912 643.2  16.59  0.000
## 960  -302.572 643.3  16.70  0.000
## 1024 -301.184 643.4  16.78  0.000
## 3898 -305.529 643.7  17.10  0.000
## 1892 -306.959 643.9  17.29  0.000
## 3004 -302.899 644.0  17.35  0.000
## 3902 -304.342 644.1  17.45  0.000
## 1920 -303.073 644.3  17.70  0.000
## 1856 -304.508 644.4  17.78  0.000
## 3068 -301.695 644.4  17.80  0.000
## 4006 -304.642 644.7  18.05  0.000
## 4016 -301.836 644.7  18.08  0.000
## 4004 -304.683 644.8  18.13  0.000
## 1022 -303.344 644.9  18.24  0.000
## 1910 -306.124 644.9  18.29  0.000
## 3066 -303.440 645.1  18.43  0.000
## 1894 -307.635 645.3  18.64  0.000
## 1900 -306.370 645.4  18.78  0.000
## 1914 -306.379 645.4  18.80  0.000
## 1898 -307.739 645.5  18.85  0.000
## 1896 -306.481 645.6  19.00  0.000
## 954  -306.587 645.8  19.21  0.000
## 3008 -302.493 646.0  19.39  0.000
## 3072 -301.095 646.1  19.52  0.000
## 1966 -305.433 646.3  19.63  0.000
## 1958 -307.251 647.2  20.54  0.000
## 4008 -304.539 647.3  20.63  0.000
## 1842 -310.028 647.4  20.82  0.000
## 1904 -306.048 647.5  20.86  0.000
## 1918 -306.119 647.6  21.00  0.000
## 3070 -303.324 647.7  21.05  0.000
## 1902 -307.538 647.7  21.12  0.000
## 1724 -306.179 647.8  21.12  0.000
## 3884 -307.762 648.2  21.56  0.000
## 958  -306.561 648.5  21.89  0.000
## 1968 -305.168 648.5  21.89  0.000
## 3002 -306.570 648.5  21.91  0.000
## 1728 -305.427 649.0  22.41  0.000
## 3888 -306.850 649.1  22.47  0.000
## 1002 -308.398 649.5  22.84  0.000
## 1960 -307.191 649.8  23.15  0.000
## 1850 -309.895 649.8  23.16  0.000
## 1954 -309.921 649.8  23.22  0.000
## 3772 -305.889 650.0  23.33  0.000
## 1010 -308.673 650.0  23.39  0.000
## 1846 -310.021 650.0  23.41  0.000
## 1788 -306.170 650.5  23.89  0.000
## 1962 -308.938 650.5  23.92  0.000
## 3876 -310.287 650.6  23.95  0.000
## 1964 -307.608 650.6  23.98  0.000
## 3882 -310.427 650.9  24.23  0.000
## 1956 -309.172 651.0  24.38  0.000
## 1014 -307.821 651.0  24.41  0.000
## 3874 -311.860 651.1  24.48  0.000
## 3006 -306.558 651.3  24.67  0.000
## 3880 -309.427 651.5  24.89  0.000
## 1016 -306.679 651.5  24.91  0.000
## 3058 -308.120 651.6  25.01  0.000
## 1716 -309.489 651.6  25.02  0.000
## 1004 -308.196 651.8  25.16  0.000
## 1792 -305.378 651.8  25.16  0.000
## 1012 -308.198 651.8  25.16  0.000
## 3776 -305.385 651.8  25.18  0.000
## 1006 -308.306 652.0  25.38  0.000
## 948  -309.740 652.1  25.52  0.000
## 3050 -308.390 652.2  25.55  0.000
## 1854 -309.895 652.5  25.83  0.000
## 3886 -309.922 652.5  25.88  0.000
## 952  -308.584 652.6  25.93  0.000
## 3878 -311.317 652.6  26.01  0.000
## 3836 -305.850 652.7  26.11  0.000
## 1772 -308.679 652.8  26.12  0.000
## 1712 -308.682 652.8  26.13  0.000
## 946  -311.431 652.9  26.23  0.000
## 3060 -307.468 653.1  26.49  0.000
## 1710 -310.233 653.1  26.51  0.000
## 3756 -308.887 653.2  26.54  0.000
## 1726 -308.897 653.2  26.56  0.000
## 1776 -307.538 653.3  26.63  0.000
## 1720 -308.966 653.3  26.70  0.000
## 2996 -309.099 653.6  26.96  0.000
## 3062 -307.756 653.7  27.07  0.000
## 1774 -309.300 654.0  27.37  0.000
## 3820 -307.938 654.1  27.43  0.000
## 1008 -307.999 654.2  27.55  0.000
## 3764 -309.424 654.2  27.61  0.000
## 3760 -308.057 654.3  27.67  0.000
## 1708 -310.829 654.3  27.70  0.000
## 3064 -306.645 654.3  27.70  0.000
## 1780 -309.484 654.4  27.73  0.000
## 3052 -308.191 654.6  27.94  0.000
## 3840 -305.322 654.6  27.97  0.000
## 3054 -308.213 654.6  27.98  0.000
## 1702 -312.420 654.8  28.21  0.000
## 1828 -313.756 654.9  28.28  0.000
## 2994 -311.123 654.9  28.28  0.000
## 950  -311.228 655.1  28.50  0.000
## 1718 -311.273 655.2  28.58  0.000
## 3000 -308.532 655.2  28.62  0.000
## 3758 -309.997 655.4  28.76  0.000
## 1764 -311.370 655.4  28.78  0.000
## 1704 -311.441 655.5  28.92  0.000
## 3824 -307.318 655.7  29.04  0.000
## 1790 -308.821 655.8  29.20  0.000
## 3774 -308.895 656.0  29.35  0.000
## 1766 -311.653 656.0  29.35  0.000
## 1784 -308.935 656.1  29.42  0.000
## 3768 -308.964 656.1  29.48  0.000
## 1700 -313.057 656.1  29.49  0.000
## 1836 -313.074 656.1  29.52  0.000
## 1768 -310.545 656.5  29.86  0.000
## 3748 -311.940 656.5  29.92  0.000
## 3822 -309.270 656.7  30.09  0.000
## 3056 -307.858 656.8  30.12  0.000
## 1770 -312.121 656.9  30.28  0.000
## 3828 -309.409 657.0  30.37  0.000
## 3750 -312.336 657.3  30.71  0.000
## 994  -313.671 657.3  30.71  0.000
## 1762 -313.724 657.4  30.82  0.000
## 1722 -312.396 657.5  30.83  0.000
## 1832 -313.746 657.5  30.86  0.000
## 3812 -311.062 657.5  30.89  0.000
## 2998 -311.099 657.6  30.96  0.000
## 1714 -313.866 657.7  31.11  0.000
## 3752 -311.191 657.8  31.15  0.000
## 1782 -311.220 657.8  31.21  0.000
## 3766 -311.253 657.9  31.27  0.000
## 1826 -316.604 658.0  31.42  0.000
## 3754 -312.723 658.1  31.49  0.000
## 998  -312.832 658.3  31.70  0.000
## 3818 -311.549 658.5  31.86  0.000
## 3838 -308.821 658.7  32.05  0.000
## 3814 -311.653 658.7  32.07  0.000
## 1840 -313.018 658.7  32.07  0.000
## 1698 -315.676 658.7  32.12  0.000
## 3770 -311.747 658.9  32.26  0.000
## 3832 -308.934 658.9  32.28  0.000
## 1706 -314.481 659.0  32.33  0.000
## 1786 -311.797 659.0  32.36  0.000
## 3746 -314.517 659.0  32.41  0.000
## 3816 -310.505 659.2  32.57  0.000
## 3042 -313.298 659.3  32.64  0.000
## 1778 -313.414 659.5  32.87  0.000
## 3810 -313.443 659.6  32.92  0.000
## 3762 -313.544 659.8  33.13  0.000
## 888  -313.634 659.9  33.31  0.000
## 996  -313.658 660.0  33.35  0.000
## 1830 -316.366 660.1  33.50  0.000
## 700  -313.844 660.4  33.73  0.000
## 1834 -316.548 660.5  33.86  0.000
## 3830 -311.192 660.6  33.94  0.000
## 1260 -314.114 660.9  34.27  0.000
## 3834 -311.365 660.9  34.28  0.000
## 1000 -312.797 661.0  34.36  0.000
## 3046 -312.823 661.0  34.41  0.000
## 2936 -313.055 661.5  34.88  0.000
## 1200 -314.437 661.5  34.91  0.000
## 2748 -313.162 661.7  35.09  0.000
## 1198 -315.898 661.8  35.17  0.000
## 3826 -313.230 661.9  35.23  0.000
## 3044 -313.297 662.0  35.36  0.000
## 896  -313.323 662.0  35.41  0.000
## 1196 -316.024 662.0  35.42  0.000
## 1264 -313.344 662.1  35.45  0.000
## 1190 -317.473 662.3  35.71  0.000
## 1252 -316.169 662.3  35.71  0.000
## 1838 -316.241 662.5  35.86  0.000
## 1516 -313.582 662.6  35.93  0.000
## 1262 -315.005 662.7  36.05  0.000
## 1188 -317.707 662.8  36.18  0.000
## 2944 -312.315 662.8  36.18  0.000
## 3244 -315.143 663.0  36.32  0.000
## 1192 -316.492 663.0  36.36  0.000
## 704  -313.807 663.0  36.38  0.000
## 1506 -316.508 663.0  36.39  0.000
## 764  -313.815 663.0  36.40  0.000
## 3308 -313.954 663.3  36.67  0.000
## 1212 -315.333 663.3  36.71  0.000
## 1508 -315.356 663.4  36.75  0.000
## 1254 -316.718 663.4  36.81  0.000
## 1514 -315.445 663.6  36.93  0.000
## 1518 -314.100 663.6  36.97  0.000
## 1276 -314.108 663.6  36.98  0.000
## 3048 -312.790 663.8  37.14  0.000
## 1216 -314.211 663.8  37.19  0.000
## 1510 -315.593 663.9  37.23  0.000
## 1256 -315.608 663.9  37.25  0.000
## 3248 -314.294 664.0  37.35  0.000
## 1250 -318.325 664.0  37.41  0.000
## 1454 -315.689 664.0  37.42  0.000
## 1572 -319.621 664.1  37.45  0.000
## 1520 -312.980 664.1  37.51  0.000
## 824  -317.097 664.2  37.57  0.000
## 1456 -314.426 664.2  37.62  0.000
## 1446 -317.132 664.3  37.64  0.000
## 1258 -317.149 664.3  37.67  0.000
## 2812 -313.089 664.4  37.73  0.000
## 2752 -313.095 664.4  37.75  0.000
## 3246 -315.888 664.4  37.82  0.000
## 1204 -317.224 664.4  37.82  0.000
## 1214 -315.898 664.5  37.83  0.000
## 3949 -318.535 664.5  37.83  0.000
## 1522 -315.901 664.5  37.84  0.000
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## 3236 -317.245 664.5  37.86  0.000
## 872  -317.324 664.6  38.02  0.000
## 1452 -316.011 664.7  38.06  0.000
## 3620 -318.696 664.8  38.16  0.000
## 1280 -313.303 664.8  38.16  0.000
## 3312 -313.342 664.9  38.24  0.000
## 3951 -317.445 664.9  38.26  0.000
## 1588 -318.765 664.9  38.29  0.000
## 3564 -313.379 664.9  38.31  0.000
## 3238 -317.471 664.9  38.31  0.000
## 1206 -317.473 664.9  38.32  0.000
## 3300 -316.141 664.9  38.32  0.000
## 1268 -316.148 665.0  38.34  0.000
## 1530 -314.786 665.0  38.34  0.000
## 886  -317.500 665.0  38.37  0.000
## 1186 -320.109 665.1  38.43  0.000
## 1534 -313.506 665.2  38.57  0.000
## 1532 -313.512 665.2  38.58  0.000
## 1444 -317.608 665.2  38.59  0.000
## 3260 -314.935 665.3  38.64  0.000
## 1270 -316.312 665.3  38.66  0.000
## 3310 -314.954 665.3  38.67  0.000
## 1512 -314.959 665.3  38.68  0.000
## 3967 -316.353 665.4  38.74  0.000
## 1208 -316.353 665.4  38.74  0.000
## 870  -319.006 665.4  38.78  0.000
## 1448 -316.386 665.4  38.81  0.000
## 3500 -315.032 665.5  38.83  0.000
## 880  -316.401 665.5  38.84  0.000
## 1526 -315.046 665.5  38.86  0.000
## 2872 -316.423 665.5  38.89  0.000
## 3554 -316.437 665.5  38.91  0.000
## 1636 -319.085 665.6  38.93  0.000
## 3240 -316.467 665.6  38.97  0.000
## 768  -313.770 665.7  39.09  0.000
## 1266 -317.890 665.8  39.15  0.000
## 1524 -315.221 665.8  39.21  0.000
## 3302 -316.592 665.9  39.22  0.000
## 1901 -320.513 665.9  39.24  0.000
## 1194 -319.255 665.9  39.27  0.000
## 3562 -315.265 665.9  39.30  0.000
## 3556 -315.296 666.0  39.36  0.000
## 1468 -315.298 666.0  39.36  0.000
## 1274 -316.662 666.0  39.36  0.000
## 3324 -313.918 666.0  39.39  0.000
## 2928 -315.383 666.2  39.53  0.000
## 1919 -318.098 666.2  39.57  0.000
## 1580 -319.410 666.2  39.58  0.000
## 3628 -318.114 666.2  39.60  0.000
## 2934 -316.821 666.3  39.68  0.000
## 3965 -318.157 666.3  39.69  0.000
## 3566 -314.098 666.4  39.75  0.000
## 832  -316.875 666.4  39.79  0.000
## 1903 -319.515 666.4  39.79  0.000
## 3636 -318.222 666.4  39.82  0.000
## 1442 -319.540 666.5  39.84  0.000
## 1272 -315.543 666.5  39.85  0.000
## 3264 -314.164 666.5  39.88  0.000
## 3558 -315.572 666.5  39.91  0.000
## 2920 -316.937 666.5  39.91  0.000
## 3304 -315.582 666.6  39.93  0.000
## 1472 -314.189 666.6  39.93  0.000
## 1909 -320.862 666.6  39.94  0.000
## 3298 -318.302 666.6  39.98  0.000
## 1893 -322.134 666.6  39.98  0.000
## 3234 -319.610 666.6  39.98  0.000
## 1576 -319.618 666.6  40.00  0.000
## 3502 -315.626 666.6  40.02  0.000
## 3492 -316.998 666.7  40.04  0.000
## 3504 -314.250 666.7  40.06  0.000
## 3624 -318.345 666.7  40.06  0.000
## 3570 -315.663 666.7  40.09  0.000
## 3903 -318.367 666.7  40.11  0.000
## 1536 -312.857 666.7  40.12  0.000
## 1470 -315.678 666.8  40.12  0.000
## 3306 -317.046 666.8  40.13  0.000
## 1911 -319.692 666.8  40.15  0.000
## 3252 -317.060 666.8  40.16  0.000
## 748  -317.073 666.8  40.18  0.000
## 1460 -317.075 666.8  40.19  0.000
## 3578 -314.336 666.9  40.23  0.000
## 3494 -317.111 666.9  40.26  0.000
## 1462 -317.119 666.9  40.28  0.000
## 3242 -318.456 666.9  40.28  0.000
## 3568 -312.962 667.0  40.33  0.000
## 2880 -315.796 667.0  40.36  0.000
## 2918 -318.505 667.0  40.38  0.000
## 3684 -318.520 667.0  40.41  0.000
## 2816 -313.028 667.1  40.46  0.000
## 3262 -315.887 667.2  40.54  0.000
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## 1596 -318.699 667.4  40.77  0.000
## 1592 -318.699 667.4  40.77  0.000
## 878  -318.709 667.4  40.79  0.000
## 1202 -320.022 667.4  40.81  0.000
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## 2858 -335.525 698.4  71.81  0.000
## 628  -335.533 698.5  71.83  0.000
## 2014 -334.245 698.5  71.86  0.000
## 4044 -334.263 698.5  71.90  0.000
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## 3921 -341.772 698.7  72.07  0.000
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## 2006 -335.664 698.7  72.09  0.000
## 2688 -331.675 698.7  72.12  0.000
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## 1948 -335.735 698.9  72.23  0.000
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## 2004 -335.782 699.0  72.33  0.000
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## 2012 -334.551 699.1  72.48  0.000
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## 1937 -342.150 699.5  72.83  0.000
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## 3859 -342.552 700.3  73.63  0.000
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## 1952 -335.148 700.3  73.67  0.000
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## 3867 -341.424 700.3  73.72  0.000
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## 3931 -340.326 700.5  73.92  0.000
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## 1944 -336.588 700.6  73.94  0.000
## 4038 -336.638 700.7  74.04  0.000
## 1009 -337.923 700.7  74.06  0.000
## 3001 -336.677 700.7  74.12  0.000
## 1945 -341.643 700.8  74.16  0.000
## 2009 -340.446 700.8  74.16  0.000
## 2972 -336.701 700.8  74.17  0.000
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## 2929 -339.296 700.9  74.31  0.000
## 3036 -335.470 700.9  74.31  0.000
## 1397 -339.331 701.0  74.37  0.000
## 2008 -335.551 701.1  74.47  0.000
## 1707 -338.137 701.1  74.49  0.000
## 2016 -334.227 701.1  74.49  0.000
## 4048 -334.262 701.2  74.56  0.000
## 2974 -336.900 701.2  74.56  0.000
## 3627 -339.498 701.3  74.71  0.000
## 3915 -341.918 701.3  74.71  0.000
## 2867 -339.571 701.5  74.86  0.000
## 1939 -342.020 701.5  74.91  0.000
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## 3934 -337.134 701.7  75.03  0.000
## 3922 -339.663 701.7  75.04  0.000
## 1941 -342.107 701.7  75.09  0.000
## 3928 -337.163 701.7  75.09  0.000
## 4040 -335.872 701.7  75.12  0.000
## 3905 -344.454 701.8  75.14  0.000
## 2873 -339.715 701.8  75.14  0.000
## 3864 -338.498 701.8  75.21  0.000
## 1663 -337.227 701.8  75.22  0.000
## 2003 -340.975 701.8  75.22  0.000
## 1399 -338.508 701.9  75.23  0.000
## 2005 -340.980 701.9  75.23  0.000
## 1775 -335.946 701.9  75.27  0.000
## 3059 -335.948 701.9  75.27  0.000
## 1727 -335.974 701.9  75.32  0.000
## 980  -338.555 701.9  75.32  0.000
## 3687 -338.557 702.0  75.33  0.000
## 1703 -338.579 702.0  75.37  0.000
## 1986 -339.831 702.0  75.38  0.000
## 1595 -339.845 702.0  75.40  0.000
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## 3695 -337.325 702.0  75.41  0.000
## 3026 -338.604 702.0  75.42  0.000
## 3043 -337.349 702.1  75.46  0.000
## 1994 -338.626 702.1  75.46  0.000
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## 1947 -341.364 702.6  75.99  0.000
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## 1403 -338.942 702.7  76.09  0.000
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## 1949 -341.515 702.9  76.30  0.000
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## 1723 -337.878 703.1  76.52  0.000
## 2013 -340.442 703.2  76.60  0.000
## 2011 -340.443 703.2  76.60  0.000
## 3030 -337.918 703.2  76.60  0.000
## 3914 -340.479 703.3  76.67  0.000
## 1988 -339.236 703.3  76.68  0.000
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## 3907 -344.323 703.8  77.17  0.000
## 1998 -338.216 703.8  77.20  0.000
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## 1943 -342.016 703.9  77.30  0.000
## 1383 -340.813 704.0  77.34  0.000
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## 1990 -339.621 704.1  77.45  0.000
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## 2007 -340.973 704.3  77.66  0.000
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## 1985 -344.829 704.8  78.18  0.000
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## 1881 -344.914 705.0  78.36  0.000
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## 1951 -341.340 705.0  78.39  0.000
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## 1635 -342.887 705.7  79.04  0.000
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## 2015 -340.441 705.7  79.09  0.000
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## 1987 -344.251 706.0  79.37  0.000
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## 1993 -344.293 706.1  79.46  0.000
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## 1989 -344.623 706.7  80.12  0.000
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## 3971 -344.857 707.2  80.59  0.000
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## 1885 -344.883 707.3  80.64  0.000
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## 1819 -346.078 707.3  80.68  0.000
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## 1815 -346.084 707.3  80.70  0.000
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## 881  -343.768 707.4  80.80  0.000
## 1991 -343.819 707.5  80.91  0.000
## 1876 -342.597 707.5  80.91  0.000
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## 2346 -341.437 707.7  81.08  0.000
## 1995 -343.913 707.7  81.09  0.000
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## 1395 -342.696 707.7  81.11  0.000
## 2901 -346.289 707.7  81.11  0.000
## 1997 -343.923 707.7  81.11  0.000
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## 1882 -343.050 708.4  81.81  0.000
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## 3175 -343.104 708.5  81.92  0.000
## 1887 -344.338 708.6  81.94  0.000
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## 1315 -345.562 708.6  82.00  0.000
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## 3131 -343.143 708.6  82.00  0.000
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## 3650 -369.195 755.9 129.26  0.000
## 1601 -373.842 756.1 129.46  0.000
## 3166 -366.953 756.2 129.62  0.000
## 3653 -371.703 756.3 129.64  0.000
## 1606 -369.415 756.3 129.70  0.000
## 1565 -371.775 756.4 129.78  0.000
## 1610 -369.464 756.4 129.80  0.000
## 3150 -368.316 756.5 129.90  0.000
## 3613 -370.697 756.5 129.92  0.000
## 1602 -370.700 756.6 129.93  0.000
## 3598 -368.343 756.6 129.95  0.000
## 1630 -367.161 756.7 130.03  0.000
## 1566 -368.433 756.8 130.13  0.000
## 1562 -369.702 756.9 130.28  0.000
## 1025 -376.401 756.9 130.29  0.000
## 3658 -368.655 757.2 130.58  0.000
## 3614 -367.442 757.2 130.60  0.000
## 1614 -368.714 757.3 130.70  0.000
## 3654 -368.722 757.3 130.71  0.000
## 3661 -371.144 757.4 130.82  0.000
## 3678 -366.438 757.7 131.09  0.000
## 1561 -373.621 757.8 131.22  0.000
## 1537 -375.982 758.2 131.58  0.000
## 65   -377.250 758.6 131.99  0.000
## 1041 -376.264 758.8 132.14  0.000
## 3662 -368.313 759.0 132.34  0.000
## 594  -372.242 759.6 133.01  0.000
## 577  -376.809 759.9 133.23  0.000
## 593  -375.770 759.9 133.31  0.000
## 2    -375.859 760.1 133.49  0.000
## 82   -373.673 760.2 133.58  0.000
## 73   -377.002 760.2 133.61  0.000
## 81   -377.011 760.3 133.63  0.000
## 1553 -375.980 760.4 133.73  0.000
## 2113 -377.064 760.4 133.74  0.000
## 69   -377.222 760.7 134.05  0.000
## 2049 -378.287 760.7 134.07  0.000
## 66   -375.079 760.8 134.14  0.000
## 10   -375.449 761.5 134.88  0.000
## 585  -376.572 761.5 134.92  0.000
## 1    -379.828 761.7 135.07  0.000
## 514  -375.568 761.7 135.11  0.000
## 74   -374.455 761.8 135.14  0.000
## 2625 -376.735 761.9 135.24  0.000
## 513  -378.882 761.9 135.25  0.000
## 2129 -376.743 761.9 135.26  0.000
## 598  -372.211 761.9 135.29  0.000
## 602  -372.216 761.9 135.30  0.000
## 2641 -375.678 762.0 135.34  0.000
## 2642 -372.238 762.0 135.35  0.000
## 581  -376.804 762.0 135.38  0.000
## 2561 -377.915 762.1 135.44  0.000
## 18   -375.744 762.1 135.47  0.000
## 597  -375.755 762.1 135.49  0.000
## 601  -375.767 762.1 135.51  0.000
## 5    -379.026 762.2 135.54  0.000
## 90   -373.512 762.2 135.55  0.000
## 89   -376.891 762.2 135.55  0.000
## 6    -375.797 762.2 135.57  0.000
## 2050 -375.806 762.2 135.59  0.000
## 2121 -376.961 762.3 135.70  0.000
## 77   -376.983 762.4 135.74  0.000
## 85   -376.993 762.4 135.76  0.000
## 2117 -377.019 762.4 135.81  0.000
## 2130 -373.670 762.5 135.87  0.000
## 86   -373.673 762.5 135.87  0.000
## 578  -374.825 762.5 135.88  0.000
## 17   -379.228 762.6 135.95  0.000
## 2065 -378.246 762.7 136.10  0.000
## 2053 -378.266 762.8 136.14  0.000
## 2057 -378.283 762.8 136.18  0.000
## 9    -379.376 762.9 136.24  0.000
## 70   -375.069 763.0 136.37  0.000
## 2114 -375.078 763.0 136.39  0.000
## 517  -378.399 763.0 136.41  0.000
## 522  -375.155 763.2 136.54  0.000
## 521  -378.479 763.2 136.57  0.000
## 530  -375.218 763.3 136.67  0.000
## 25   -378.557 763.4 136.72  0.000
## 586  -374.204 763.6 136.94  0.000
## 589  -376.508 763.6 136.99  0.000
## 2645 -375.418 763.7 137.06  0.000
## 21   -378.730 763.7 137.07  0.000
## 26   -375.436 763.7 137.10  0.000
## 14   -375.442 763.7 137.11  0.000
## 2633 -376.572 763.8 137.12  0.000
## 2058 -375.448 763.8 137.13  0.000
## 2133 -376.596 763.8 137.17  0.000
## 529  -378.785 763.8 137.18  0.000
## 2122 -374.375 763.9 137.28  0.000
## 518  -375.526 763.9 137.28  0.000
## 2562 -375.538 763.9 137.31  0.000
## 2629 -376.701 764.0 137.38  0.000
## 78   -374.433 764.0 137.39  0.000
## 2137 -376.742 764.1 137.46  0.000
## 2649 -375.649 764.2 137.53  0.000
## 2066 -375.659 764.2 137.55  0.000
## 2569 -377.890 764.2 137.55  0.000
## 13   -378.980 764.2 137.57  0.000
## 2565 -377.902 764.2 137.58  0.000
## 22   -375.675 764.2 137.58  0.000
## 2577 -377.909 764.2 137.59  0.000
## 606  -372.162 764.2 137.59  0.000
## 2650 -372.195 764.3 137.66  0.000
## 2125 -376.851 764.3 137.68  0.000
## 2646 -372.209 764.3 137.69  0.000
## 605  -375.736 764.3 137.70  0.000
## 93   -376.884 764.4 137.75  0.000
## 2054 -375.785 764.4 137.80  0.000
## 94   -373.495 764.5 137.86  0.000
## 2138 -373.499 764.5 137.87  0.000
## 582  -374.822 764.8 138.17  0.000
## 2073 -378.202 764.8 138.18  0.000
## 2626 -374.825 764.8 138.18  0.000
## 2134 -373.667 764.8 138.21  0.000
## 2069 -378.234 764.9 138.24  0.000
## 2061 -378.253 764.9 138.28  0.000
## 537  -378.260 764.9 138.29  0.000
## 525  -378.309 765.0 138.39  0.000
## 533  -378.367 765.1 138.51  0.000
## 538  -375.020 765.2 138.57  0.000
## 2118 -375.068 765.3 138.66  0.000
## 29   -378.498 765.4 138.77  0.000
## 2578 -375.153 765.5 138.83  0.000
## 2570 -375.154 765.5 138.84  0.000
## 526  -375.154 765.5 138.84  0.000
## 534  -375.174 765.5 138.88  0.000
## 2634 -374.088 765.7 139.05  0.000
## 2637 -376.464 765.8 139.16  0.000
## 590  -374.168 765.8 139.21  0.000
## 2653 -375.412 766.0 139.35  0.000
## 30   -375.426 766.0 139.38  0.000
## 2074 -375.431 766.0 139.39  0.000
## 2141 -376.583 766.0 139.40  0.000
## 2062 -375.442 766.0 139.41  0.000
## 2566 -375.521 766.2 139.57  0.000
## 2126 -374.375 766.2 139.62  0.000
## 2573 -377.861 766.3 139.70  0.000
## 2585 -377.890 766.4 139.76  0.000
## 2581 -377.891 766.4 139.76  0.000
## 2070 -375.646 766.4 139.82  0.000
## 2654 -372.161 766.7 140.04  0.000
## 2142 -373.492 766.9 140.25  0.000
## 2077 -378.175 767.0 140.33  0.000
## 541  -378.200 767.0 140.38  0.000
## 2630 -374.816 767.1 140.51  0.000
## 2586 -375.013 767.5 140.90  0.000
## 542  -375.014 767.5 140.90  0.000
## 2582 -375.147 767.8 141.17  0.000
## 2574 -375.150 767.8 141.17  0.000
## 2638 -374.087 768.1 141.44  0.000
## 2078 -375.426 768.4 141.72  0.000
## 2589 -377.861 768.6 141.95  0.000
## 2590 -375.011 769.9 143.29  0.000
## Models ranked by AICc(x)
top <- weightable(res_stimuli_modality)
top <- top[top$aicc <= min(top$aicc) + 2,]
top
##                                                                                                                                                                                                                                                                    model
## 1                                       d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## 2                  d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## 3                      d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video
## 4 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video
## 5                                                 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video
## 6                            d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video
##       aicc    weights
## 1 628.1178 0.11822538
## 2 628.1178 0.11822538
## 3 629.6108 0.05604127
## 4 629.6108 0.05604127
## 5 629.6825 0.05406772
## 6 629.6825 0.05406772
summary(res_stimuli_modality@objects[[1]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -294.9680   614.1518   621.9360   664.3994   628.1178   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 89) = 614.1518, p-val < .0001
## 
## Test of Moderators (coefficients 2:16):
## QM(df = 15) = 169.7196, p-val < .0001
## 
## Model Results:
## 
##                                             estimate      se     zval    pval 
## intrcpt                                      -0.2346  0.2338  -1.0033  0.3157 
## agent_argument_type_cleannoun_phrase         -0.0189  0.1512  -0.1251  0.9005 
## agent_argument_type_cleanpronoun             -1.0490  0.1746  -6.0090  <.0001 
## agent_argument_type_cleanvarying_agent        0.3263  0.1596   2.0446  0.0409 
## patient_argument_type_cleannoun              -0.1362  0.1025  -1.3284  0.1841 
## patient_argument_type_cleannoun_phrase        1.0182  0.1517   6.7107  <.0001 
## patient_argument_type_cleanpronoun            1.0479  0.1475   7.1042  <.0001 
## patient_argument_type_cleanvarying_patient   -0.6836  0.1723  -3.9679  <.0001 
## stimuli_actorperson                          -0.5913  0.1249  -4.7352  <.0001 
## stimuli_modalityvideo                         0.9659  0.1515   6.3765  <.0001 
## presentation_typeimmediate_after              0.7902  0.1866   4.2361  <.0001 
## presentation_typesimultaneous                 0.5727  0.1857   3.0842  0.0020 
## test_mass_or_distributedmass                  0.4082  0.1024   3.9845  <.0001 
## character_identificationyes                   0.2318  0.0977   2.3717  0.0177 
## n_repetitions_sentence                        0.0220  0.0095   2.3166  0.0205 
## n_repetitions_video                          -0.1757  0.0349  -5.0278  <.0001 
##                                               ci.lb    ci.ub 
## intrcpt                                     -0.6928   0.2236      
## agent_argument_type_cleannoun_phrase        -0.3153   0.2774      
## agent_argument_type_cleanpronoun            -1.3912  -0.7069  *** 
## agent_argument_type_cleanvarying_agent       0.0135   0.6391    * 
## patient_argument_type_cleannoun             -0.3371   0.0647      
## patient_argument_type_cleannoun_phrase       0.7208   1.3156  *** 
## patient_argument_type_cleanpronoun           0.7588   1.3371  *** 
## patient_argument_type_cleanvarying_patient  -1.0212  -0.3459  *** 
## stimuli_actorperson                         -0.8360  -0.3465  *** 
## stimuli_modalityvideo                        0.6690   1.2628  *** 
## presentation_typeimmediate_after             0.4246   1.1559  *** 
## presentation_typesimultaneous                0.2088   0.9367   ** 
## test_mass_or_distributedmass                 0.2074   0.6090  *** 
## character_identificationyes                  0.0402   0.4234    * 
## n_repetitions_sentence                       0.0034   0.0405    * 
## n_repetitions_video                         -0.2442  -0.1072  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_stimuli_modality, type="s")
summary(res_stimuli_modality@objects[[2]])
## 
## Multivariate Meta-Analysis Model (k = 105; method: ML)
## 
##    logLik   Deviance        AIC        BIC       AICc 
## -294.9680   614.1518   621.9360   664.3994   628.1178   
## 
## Variance Components: none
## 
## Test for Residual Heterogeneity:
## QE(df = 89) = 614.1518, p-val < .0001
## 
## Test of Moderators (coefficients 2:16):
## QM(df = 15) = 169.7196, p-val < .0001
## 
## Model Results:
## 
##                                         estimate      se     zval    pval 
## intrcpt                                  -0.2346  0.2338  -1.0033  0.3157 
## sentence_structuretransitive             -0.6836  0.1723  -3.9679  <.0001 
## agent_argument_type_cleannoun_phrase     -0.0189  0.1512  -0.1251  0.9005 
## agent_argument_type_cleanpronoun         -1.0490  0.1746  -6.0090  <.0001 
## agent_argument_type_cleanvarying_agent    0.3263  0.1596   2.0446  0.0409 
## patient_argument_type_cleannoun           0.5474  0.1640   3.3379  0.0008 
## patient_argument_type_cleannoun_phrase    1.7018  0.2279   7.4665  <.0001 
## patient_argument_type_cleanpronoun        1.7315  0.2302   7.5219  <.0001 
## stimuli_actorperson                      -0.5913  0.1249  -4.7352  <.0001 
## stimuli_modalityvideo                     0.9659  0.1515   6.3765  <.0001 
## presentation_typeimmediate_after          0.7902  0.1866   4.2361  <.0001 
## presentation_typesimultaneous             0.5727  0.1857   3.0842  0.0020 
## test_mass_or_distributedmass              0.4082  0.1024   3.9845  <.0001 
## character_identificationyes               0.2318  0.0977   2.3717  0.0177 
## n_repetitions_sentence                    0.0220  0.0095   2.3166  0.0205 
## n_repetitions_video                      -0.1757  0.0349  -5.0278  <.0001 
##                                           ci.lb    ci.ub 
## intrcpt                                 -0.6928   0.2236      
## sentence_structuretransitive            -1.0212  -0.3459  *** 
## agent_argument_type_cleannoun_phrase    -0.3153   0.2774      
## agent_argument_type_cleanpronoun        -1.3912  -0.7069  *** 
## agent_argument_type_cleanvarying_agent   0.0135   0.6391    * 
## patient_argument_type_cleannoun          0.2260   0.8689  *** 
## patient_argument_type_cleannoun_phrase   1.2551   2.1485  *** 
## patient_argument_type_cleanpronoun       1.2803   2.1827  *** 
## stimuli_actorperson                     -0.8360  -0.3465  *** 
## stimuli_modalityvideo                    0.6690   1.2628  *** 
## presentation_typeimmediate_after         0.4246   1.1559  *** 
## presentation_typesimultaneous            0.2088   0.9367   ** 
## test_mass_or_distributedmass             0.2074   0.6090  *** 
## character_identificationyes              0.0402   0.4234    * 
## n_repetitions_sentence                   0.0034   0.0405    * 
## n_repetitions_video                     -0.2442  -0.1072  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(res_stimuli_modality, type="s")

eval(metafor:::.glmulti)
coef(res_stimuli_modality)
##                                                 Estimate Uncond. variance
## mean_age                                    0.0000427903     8.242971e-09
## practice_phaseyes                           0.0710394305     1.069194e-02
## sentence_structuretransitive               -0.3141608853     1.127777e-01
## patient_argument_type_cleanvarying_patient -0.3141608853     1.127777e-01
## character_identificationyes                 0.1134302294     1.586680e-02
## n_repetitions_sentence                      0.0144506224     1.490095e-04
## intrcpt                                    -0.1984816941     8.726582e-02
## agent_argument_type_cleannoun_phrase        0.0055412423     2.329052e-02
## agent_argument_type_cleanpronoun           -1.0413154409     3.238753e-02
## agent_argument_type_cleanvarying_agent      0.3026394206     2.732623e-02
## patient_argument_type_cleannoun             0.1864858684     1.170563e-01
## patient_argument_type_cleannoun_phrase      1.3309291031     1.359046e-01
## patient_argument_type_cleanpronoun          1.3460888937     1.352170e-01
## stimuli_actorperson                        -0.6325170153     1.726520e-02
## stimuli_modalityvideo                       0.9470042263     2.341994e-02
## presentation_typeimmediate_after            0.7263806611     4.262262e-02
## presentation_typesimultaneous               0.4616392679     4.485019e-02
## test_mass_or_distributedmass                0.4360120459     1.188102e-02
## n_repetitions_video                        -0.1502661101     1.935324e-03
##                                            Nb models Importance
## mean_age                                          16  0.2682378
## practice_phaseyes                                 16  0.4267868
## sentence_structuretransitive                      16  0.5000000
## patient_argument_type_cleanvarying_patient        16  0.5000000
## character_identificationyes                       16  0.5751023
## n_repetitions_sentence                            16  0.7076217
## intrcpt                                           32  1.0000000
## agent_argument_type_cleannoun_phrase              32  1.0000000
## agent_argument_type_cleanpronoun                  32  1.0000000
## agent_argument_type_cleanvarying_agent            32  1.0000000
## patient_argument_type_cleannoun                   32  1.0000000
## patient_argument_type_cleannoun_phrase            32  1.0000000
## patient_argument_type_cleanpronoun                32  1.0000000
## stimuli_actorperson                               32  1.0000000
## stimuli_modalityvideo                             32  1.0000000
## presentation_typeimmediate_after                  32  1.0000000
## presentation_typesimultaneous                     32  1.0000000
## test_mass_or_distributedmass                      32  1.0000000
## n_repetitions_video                               32  1.0000000
##                                            +/- (alpha=0.05)
## mean_age                                       0.0001779467
## practice_phaseyes                              0.2026638430
## sentence_structuretransitive                   0.6582029183
## patient_argument_type_cleanvarying_patient     0.6582029183
## character_identificationyes                    0.2468839124
## n_repetitions_sentence                         0.0239251759
## intrcpt                                        0.5789888110
## agent_argument_type_cleannoun_phrase           0.2991146441
## agent_argument_type_cleanpronoun               0.3527255930
## agent_argument_type_cleanvarying_agent         0.3239947489
## patient_argument_type_cleannoun                0.6705720850
## patient_argument_type_cleannoun_phrase         0.7225454772
## patient_argument_type_cleanpronoun             0.7207152498
## stimuli_actorperson                            0.2575336209
## stimuli_modalityvideo                          0.2999445450
## presentation_typeimmediate_after               0.4046393964
## presentation_typesimultaneous                  0.4150784923
## test_mass_or_distributedmass                   0.2136362809
## n_repetitions_video                            0.0862233568
mmi <- as.data.frame(coef(res_stimuli_modality))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)
##                                            Estimate Std. Error z value Pr(>|z|)
## intrcpt                                     -0.1985     0.2954 -0.6719   0.5017
## agent_argument_type_cleannoun_phrase         0.0055     0.1526  0.0363   0.9710
## agent_argument_type_cleanpronoun            -1.0413     0.1800 -5.7862   0.0000
## agent_argument_type_cleanvarying_agent       0.3026     0.1653  1.8308   0.0671
## patient_argument_type_cleannoun              0.1865     0.3421  0.5451   0.5857
## patient_argument_type_cleannoun_phrase       1.3309     0.3687  3.6103   0.0003
## patient_argument_type_cleanpronoun           1.3461     0.3677  3.6606   0.0003
## stimuli_actorperson                         -0.6325     0.1314 -4.8138   0.0000
## stimuli_modalityvideo                        0.9470     0.1530  6.1881   0.0000
## presentation_typeimmediate_after             0.7264     0.2065  3.5184   0.0004
## presentation_typesimultaneous                0.4616     0.2118  2.1798   0.0293
## test_mass_or_distributedmass                 0.4360     0.1090  4.0001   0.0001
## n_repetitions_video                         -0.1503     0.0440 -3.4157   0.0006
## n_repetitions_sentence                       0.0145     0.0122  1.1838   0.2365
## character_identificationyes                  0.1134     0.1260  0.9005   0.3679
## patient_argument_type_cleanvarying_patient  -0.3142     0.3358 -0.9355   0.3495
## sentence_structuretransitive                -0.3142     0.3358 -0.9355   0.3495
## practice_phaseyes                            0.0710     0.1034  0.6870   0.4921
## mean_age                                     0.0000     0.0001  0.4713   0.6374
##                                              ci.lb   ci.ub Importance
## intrcpt                                    -0.7775  0.3805     1.0000
## agent_argument_type_cleannoun_phrase       -0.2936  0.3047     1.0000
## agent_argument_type_cleanpronoun           -1.3940 -0.6886     1.0000
## agent_argument_type_cleanvarying_agent     -0.0214  0.6266     1.0000
## patient_argument_type_cleannoun            -0.4841  0.8571     1.0000
## patient_argument_type_cleannoun_phrase      0.6084  2.0535     1.0000
## patient_argument_type_cleanpronoun          0.6254  2.0668     1.0000
## stimuli_actorperson                        -0.8901 -0.3750     1.0000
## stimuli_modalityvideo                       0.6471  1.2469     1.0000
## presentation_typeimmediate_after            0.3217  1.1310     1.0000
## presentation_typesimultaneous               0.0466  0.8767     1.0000
## test_mass_or_distributedmass                0.2224  0.6496     1.0000
## n_repetitions_video                        -0.2365 -0.0640     1.0000
## n_repetitions_sentence                     -0.0095  0.0384     0.7076
## character_identificationyes                -0.1335  0.3603     0.5751
## patient_argument_type_cleanvarying_patient -0.9724  0.3440     0.5000
## sentence_structuretransitive               -0.9724  0.3440     0.5000
## practice_phaseyes                          -0.1316  0.2737     0.4268
## mean_age                                   -0.0001  0.0002     0.2682